7.2
Load data
set.seed(200)
trainingData = mlbench.friedman1(200, sd=1)
trainingData$x = data.frame(trainingData$x)
testData = mlbench.friedman1(5000, sd=1)
testData$x = data.frame(testData$x)
Tune several model on this data
model.eval = function(modelmethod, gridSearch = NULL)
{
Model = train(x = trainingData$x, y = trainingData$y, method = modelmethod, tuneGrid = gridSearch, preProcess = c('center', 'scale'), trControl = trainControl(method='cv'))
Pred = predict(Model, newdata = testData$x)
modelperf = postResample(Pred, testData$y)
print(modelperf)
}
1] K-Nearest Neighbors -
perfknn = model.eval('knn')
## RMSE Rsquared MAE
## 3.1172319 0.6556622 2.4899907
2] Neural Net -
nnetGrid = expand.grid(decay = c(0,0.01, .1), size = c(1:10))
perfnn = model.eval('nnet', nnetGrid)
## # weights: 13
## initial value 39128.937399
## final value 36633.902952
## converged
## # weights: 13
## initial value 39188.722575
## iter 10 value 36668.073038
## iter 20 value 36635.177218
## iter 30 value 36634.708002
## final value 36634.689761
## converged
## # weights: 13
## initial value 38816.897592
## iter 10 value 36639.910226
## final value 36639.336370
## converged
## # weights: 25
## initial value 38154.900808
## final value 36633.902952
## converged
## # weights: 25
## initial value 38493.520425
## iter 10 value 36666.890605
## iter 20 value 36635.367310
## iter 30 value 36634.595662
## iter 40 value 36634.535861
## final value 36634.534858
## converged
## # weights: 25
## initial value 39537.826824
## iter 10 value 36639.674803
## final value 36638.370967
## converged
## # weights: 37
## initial value 38043.401836
## final value 36633.902952
## converged
## # weights: 37
## initial value 38593.990554
## iter 10 value 36639.985921
## iter 20 value 36634.721840
## iter 30 value 36634.467408
## final value 36634.451453
## converged
## # weights: 37
## initial value 37711.091350
## iter 10 value 36639.511344
## final value 36637.824946
## converged
## # weights: 49
## initial value 39440.309000
## final value 36633.902952
## converged
## # weights: 49
## initial value 38029.198297
## iter 10 value 36672.796013
## iter 20 value 36635.542221
## iter 30 value 36634.502277
## iter 40 value 36634.401994
## final value 36634.397060
## converged
## # weights: 49
## initial value 39926.941027
## iter 10 value 36648.929613
## iter 20 value 36637.455454
## final value 36637.453922
## converged
## # weights: 61
## initial value 39988.562481
## final value 36633.902952
## converged
## # weights: 61
## initial value 39599.887800
## iter 10 value 36698.635143
## iter 20 value 36636.693953
## iter 30 value 36634.798090
## iter 40 value 36634.364799
## final value 36634.357198
## converged
## # weights: 61
## initial value 39680.755050
## iter 10 value 36655.519618
## iter 20 value 36637.175829
## final value 36637.174806
## converged
## # weights: 73
## initial value 38045.878631
## final value 36633.902952
## converged
## # weights: 73
## initial value 39244.706377
## iter 10 value 36647.360996
## iter 20 value 36634.454524
## iter 30 value 36634.326455
## final value 36634.323890
## converged
## # weights: 73
## initial value 39354.052854
## iter 10 value 36656.093009
## iter 20 value 36636.952314
## final value 36636.951822
## converged
## # weights: 85
## initial value 38511.464855
## final value 36633.902952
## converged
## # weights: 85
## initial value 40021.381697
## iter 10 value 36702.181616
## iter 20 value 36636.473928
## iter 30 value 36634.522637
## iter 40 value 36634.303678
## final value 36634.299091
## converged
## # weights: 85
## initial value 39997.196337
## iter 10 value 36659.526038
## iter 20 value 36636.769323
## final value 36636.766910
## converged
## # weights: 97
## initial value 40244.392358
## final value 36633.902952
## converged
## # weights: 97
## initial value 39943.609128
## iter 10 value 36698.110860
## iter 20 value 36636.351352
## iter 30 value 36634.501556
## iter 40 value 36634.285650
## final value 36634.277681
## converged
## # weights: 97
## initial value 38653.611671
## iter 10 value 36661.098153
## iter 20 value 36636.610457
## final value 36636.608715
## converged
## # weights: 109
## initial value 38552.248655
## final value 36633.902952
## converged
## # weights: 109
## initial value 38170.924200
## iter 10 value 36643.878144
## iter 20 value 36634.617017
## iter 30 value 36634.292632
## final value 36634.258348
## converged
## # weights: 109
## initial value 37708.487124
## iter 10 value 36650.603941
## iter 20 value 36636.488123
## final value 36636.471182
## converged
## # weights: 121
## initial value 38824.059420
## final value 36633.902952
## converged
## # weights: 121
## initial value 39937.556967
## iter 10 value 36643.687061
## iter 20 value 36634.290687
## iter 30 value 36634.242637
## final value 36634.242005
## converged
## # weights: 121
## initial value 39135.588137
## iter 10 value 36669.883297
## iter 20 value 36636.351010
## final value 36636.349712
## converged
## # weights: 13
## initial value 38462.869706
## final value 36997.484107
## converged
## # weights: 13
## initial value 39579.971289
## iter 10 value 37030.974501
## iter 20 value 36998.700617
## iter 30 value 36998.307294
## final value 36998.271210
## converged
## # weights: 13
## initial value 39734.196170
## iter 10 value 37003.597092
## final value 37002.922422
## converged
## # weights: 25
## initial value 39871.433806
## final value 36997.484107
## converged
## # weights: 25
## initial value 39897.310381
## iter 10 value 37038.802414
## iter 20 value 36998.844140
## iter 30 value 36998.157982
## iter 40 value 36998.116562
## iter 40 value 36998.116492
## iter 40 value 36998.116462
## final value 36998.116462
## converged
## # weights: 25
## initial value 38173.771632
## iter 10 value 37005.392924
## final value 37001.956044
## converged
## # weights: 37
## initial value 40350.285403
## final value 36997.484107
## converged
## # weights: 37
## initial value 40358.581100
## iter 10 value 37034.523656
## iter 20 value 36999.021320
## iter 30 value 36998.093830
## iter 40 value 36998.034324
## final value 36998.032931
## converged
## # weights: 37
## initial value 40169.061918
## iter 10 value 37003.778391
## final value 37001.409539
## converged
## # weights: 49
## initial value 40444.676983
## final value 36997.484107
## converged
## # weights: 49
## initial value 39706.262817
## iter 10 value 37059.693739
## iter 20 value 36999.127320
## iter 30 value 36998.075664
## iter 40 value 36997.979843
## final value 36997.978306
## converged
## # weights: 49
## initial value 38770.956372
## iter 10 value 37006.408630
## iter 20 value 37001.039079
## final value 37001.037963
## converged
## # weights: 61
## initial value 40417.971961
## final value 36997.484107
## converged
## # weights: 61
## initial value 39306.043884
## iter 10 value 37054.117342
## iter 20 value 36999.281865
## iter 30 value 36997.994456
## iter 40 value 36997.939876
## final value 36997.937690
## converged
## # weights: 61
## initial value 39334.268883
## iter 10 value 37019.941177
## iter 20 value 37000.763553
## final value 37000.758766
## converged
## # weights: 73
## initial value 40714.796083
## final value 36997.484107
## converged
## # weights: 73
## initial value 39420.175096
## iter 10 value 37063.067095
## iter 20 value 36999.334624
## iter 30 value 36998.032131
## iter 40 value 36997.910304
## final value 36997.906039
## converged
## # weights: 73
## initial value 39333.336416
## iter 10 value 37021.981250
## iter 20 value 37000.540345
## final value 37000.535589
## converged
## # weights: 85
## initial value 40295.838767
## final value 36997.484107
## converged
## # weights: 85
## initial value 39458.285854
## iter 10 value 37008.531998
## iter 20 value 36997.976036
## iter 30 value 36997.883956
## final value 36997.879754
## converged
## # weights: 85
## initial value 39176.508369
## iter 10 value 37024.733712
## iter 20 value 37000.354041
## final value 37000.350461
## converged
## # weights: 97
## initial value 39679.158477
## final value 36997.484107
## converged
## # weights: 97
## initial value 40746.981571
## iter 10 value 37010.105938
## iter 20 value 36997.997136
## iter 30 value 36997.862463
## final value 36997.859248
## converged
## # weights: 97
## initial value 39183.771993
## iter 10 value 37031.091591
## iter 20 value 37000.198604
## final value 37000.192215
## converged
## # weights: 109
## initial value 38578.101230
## final value 36997.484107
## converged
## # weights: 109
## initial value 38309.522920
## iter 10 value 37008.418603
## iter 20 value 36997.992792
## iter 30 value 36997.843859
## final value 36997.839633
## converged
## # weights: 109
## initial value 39214.146432
## iter 10 value 37030.454269
## iter 20 value 37000.060226
## final value 37000.054538
## converged
## # weights: 121
## initial value 39541.323267
## final value 36997.484107
## converged
## # weights: 121
## initial value 39129.577553
## iter 10 value 37009.994913
## iter 20 value 36998.003696
## iter 30 value 36997.825593
## final value 36997.823141
## converged
## # weights: 121
## initial value 38222.925236
## iter 10 value 37028.552338
## iter 20 value 36999.937894
## final value 36999.933080
## converged
## # weights: 13
## initial value 38096.862641
## final value 36532.568282
## converged
## # weights: 13
## initial value 39354.473410
## iter 10 value 36563.711704
## iter 20 value 36533.884597
## iter 30 value 36533.387885
## final value 36533.354803
## converged
## # weights: 13
## initial value 38822.913221
## iter 10 value 36538.975184
## final value 36538.001482
## converged
## # weights: 25
## initial value 38838.158126
## final value 36532.568282
## converged
## # weights: 25
## initial value 38497.620224
## iter 10 value 36572.642886
## iter 20 value 36534.024024
## iter 30 value 36533.251857
## iter 40 value 36533.200742
## final value 36533.200092
## converged
## # weights: 25
## initial value 37973.794820
## iter 10 value 36539.399286
## final value 36537.036272
## converged
## # weights: 37
## initial value 39996.988017
## final value 36532.568282
## converged
## # weights: 37
## initial value 39070.087123
## iter 10 value 36579.169997
## iter 20 value 36534.094398
## iter 30 value 36533.155155
## iter 40 value 36533.116709
## iter 40 value 36533.116501
## iter 40 value 36533.116464
## final value 36533.116464
## converged
## # weights: 37
## initial value 39390.808546
## iter 10 value 36541.573547
## iter 20 value 36536.492154
## final value 36536.490470
## converged
## # weights: 49
## initial value 39435.382947
## final value 36532.568282
## converged
## # weights: 49
## initial value 39854.438598
## iter 10 value 36577.433436
## iter 20 value 36534.156707
## iter 30 value 36533.152156
## iter 40 value 36533.063397
## final value 36533.062450
## converged
## # weights: 49
## initial value 40146.032704
## iter 10 value 36538.723077
## iter 20 value 36536.121769
## final value 36536.119262
## converged
## # weights: 61
## initial value 39312.267577
## final value 36532.568282
## converged
## # weights: 61
## initial value 39134.834434
## iter 10 value 36592.057846
## iter 20 value 36534.366599
## iter 30 value 36533.073592
## iter 40 value 36533.024585
## final value 36533.021877
## converged
## # weights: 61
## initial value 39223.907376
## iter 10 value 36550.794396
## iter 20 value 36535.840742
## final value 36535.840168
## converged
## # weights: 73
## initial value 38535.165791
## final value 36532.568282
## converged
## # weights: 73
## initial value 38489.617624
## iter 10 value 36544.958240
## iter 20 value 36533.119264
## iter 30 value 36532.996979
## final value 36532.989640
## converged
## # weights: 73
## initial value 37924.947074
## iter 10 value 36553.638917
## iter 20 value 36535.642767
## final value 36535.617253
## converged
## # weights: 85
## initial value 39071.134069
## final value 36532.568282
## converged
## # weights: 85
## initial value 39311.797400
## iter 10 value 36546.361830
## iter 20 value 36533.090708
## iter 30 value 36532.967006
## iter 30 value 36532.966652
## iter 30 value 36532.966446
## final value 36532.966446
## converged
## # weights: 85
## initial value 38710.918841
## iter 10 value 36561.935417
## iter 20 value 36535.438425
## final value 36535.432262
## converged
## # weights: 97
## initial value 38389.553243
## final value 36532.568282
## converged
## # weights: 97
## initial value 38201.228845
## iter 10 value 36592.288405
## iter 20 value 36534.411528
## iter 30 value 36532.982832
## iter 40 value 36532.943908
## final value 36532.942221
## converged
## # weights: 97
## initial value 37921.549998
## iter 10 value 36559.308780
## iter 20 value 36535.289570
## final value 36535.274147
## converged
## # weights: 109
## initial value 38441.059294
## final value 36532.568282
## converged
## # weights: 109
## initial value 39705.833760
## iter 10 value 36605.230084
## iter 20 value 36534.964603
## iter 30 value 36533.028057
## final value 36532.925946
## converged
## # weights: 109
## initial value 39724.383272
## iter 10 value 36564.826250
## iter 20 value 36535.149726
## final value 36535.136738
## converged
## # weights: 121
## initial value 40846.378001
## final value 36532.568282
## converged
## # weights: 121
## initial value 39424.795318
## iter 10 value 36544.984145
## iter 20 value 36532.952712
## final value 36532.909079
## converged
## # weights: 121
## initial value 38546.328798
## iter 10 value 36576.153731
## iter 20 value 36535.019795
## final value 36535.015127
## converged
## # weights: 13
## initial value 40318.265147
## final value 36937.667375
## converged
## # weights: 13
## initial value 38826.446907
## iter 10 value 36968.019075
## iter 20 value 36938.971814
## iter 30 value 36938.495048
## iter 40 value 36938.455209
## iter 40 value 36938.455000
## iter 40 value 36938.454876
## final value 36938.454876
## converged
## # weights: 13
## initial value 38953.560235
## iter 10 value 36943.715174
## final value 36943.105377
## converged
## # weights: 25
## initial value 38558.818684
## final value 36937.667375
## converged
## # weights: 25
## initial value 39013.167266
## iter 10 value 36975.650107
## iter 20 value 36938.898074
## iter 30 value 36938.327977
## final value 36938.299731
## converged
## # weights: 25
## initial value 40074.359107
## iter 10 value 36942.848673
## final value 36942.139041
## converged
## # weights: 37
## initial value 38266.835237
## final value 36937.667375
## converged
## # weights: 37
## initial value 39648.854757
## iter 10 value 36989.942219
## iter 20 value 36939.480263
## iter 30 value 36938.317220
## iter 40 value 36938.219540
## final value 36938.216040
## converged
## # weights: 37
## initial value 39619.975710
## iter 10 value 36942.521117
## final value 36941.592583
## converged
## # weights: 49
## initial value 40368.594554
## final value 36937.667375
## converged
## # weights: 49
## initial value 38939.819492
## iter 10 value 36990.537492
## iter 20 value 36939.703356
## iter 30 value 36938.280672
## iter 40 value 36938.165115
## final value 36938.162085
## converged
## # weights: 49
## initial value 38675.906511
## iter 10 value 36952.632210
## iter 20 value 36941.225509
## final value 36941.220932
## converged
## # weights: 61
## initial value 39396.412191
## final value 36937.667375
## converged
## # weights: 61
## initial value 40092.862798
## iter 10 value 36946.594578
## iter 20 value 36938.221932
## iter 30 value 36938.124542
## final value 36938.120380
## converged
## # weights: 61
## initial value 40171.447822
## iter 10 value 36954.776767
## iter 20 value 36940.943585
## final value 36940.941687
## converged
## # weights: 73
## initial value 40881.139092
## final value 36937.667375
## converged
## # weights: 73
## initial value 39214.026509
## iter 10 value 37009.078821
## iter 20 value 36939.688392
## iter 30 value 36938.237982
## iter 40 value 36938.097269
## final value 36938.089993
## converged
## # weights: 73
## initial value 40450.357036
## iter 10 value 36960.295435
## iter 20 value 36940.721605
## final value 36940.718687
## converged
## # weights: 85
## initial value 39595.834366
## final value 36937.667375
## converged
## # weights: 85
## initial value 40017.895059
## iter 10 value 36951.084609
## iter 20 value 36938.382882
## iter 30 value 36938.092104
## final value 36938.063443
## converged
## # weights: 85
## initial value 40875.466657
## iter 10 value 36957.392845
## iter 20 value 36940.537235
## final value 36940.533342
## converged
## # weights: 97
## initial value 39186.329295
## final value 36937.667375
## converged
## # weights: 97
## initial value 39662.374637
## iter 10 value 36952.470695
## iter 20 value 36938.324688
## iter 30 value 36938.045100
## final value 36938.042121
## converged
## # weights: 97
## initial value 39345.596952
## iter 10 value 36968.969118
## iter 20 value 36940.385893
## final value 36940.375312
## converged
## # weights: 109
## initial value 41146.469953
## final value 36937.667375
## converged
## # weights: 109
## initial value 39349.158932
## iter 10 value 36954.112150
## iter 20 value 36938.171424
## iter 30 value 36938.023932
## final value 36938.023196
## converged
## # weights: 109
## initial value 39592.452981
## iter 10 value 36972.950213
## iter 20 value 36940.247457
## final value 36940.237663
## converged
## # weights: 121
## initial value 40354.746464
## final value 36937.667375
## converged
## # weights: 121
## initial value 38787.694707
## iter 10 value 36938.287353
## iter 20 value 36938.024684
## iter 30 value 36938.006240
## iter 30 value 36938.006149
## iter 30 value 36938.006105
## final value 36938.006105
## converged
## # weights: 121
## initial value 39384.690602
## iter 10 value 36978.085099
## iter 20 value 36940.120793
## final value 36940.116047
## converged
## # weights: 13
## initial value 38749.523093
## final value 36921.822250
## converged
## # weights: 13
## initial value 40376.065040
## iter 10 value 36945.723584
## iter 20 value 36923.051216
## iter 30 value 36922.630571
## iter 40 value 36922.609242
## iter 40 value 36922.609104
## iter 40 value 36922.609070
## final value 36922.609070
## converged
## # weights: 13
## initial value 40014.302432
## iter 10 value 36927.680079
## final value 36927.258677
## converged
## # weights: 25
## initial value 39185.816193
## final value 36921.822250
## converged
## # weights: 25
## initial value 39435.345888
## iter 10 value 36962.351273
## iter 20 value 36923.057518
## iter 30 value 36922.483193
## iter 40 value 36922.454554
## iter 40 value 36922.454447
## iter 40 value 36922.454421
## final value 36922.454421
## converged
## # weights: 25
## initial value 39251.444376
## iter 10 value 36928.147805
## final value 36926.292389
## converged
## # weights: 37
## initial value 40132.789511
## final value 36921.822250
## converged
## # weights: 37
## initial value 38194.840704
## iter 10 value 36948.994951
## iter 20 value 36923.273659
## iter 30 value 36922.420768
## iter 40 value 36922.373382
## final value 36922.372038
## converged
## # weights: 37
## initial value 40240.197153
## iter 10 value 36935.860444
## final value 36925.746085
## converged
## # weights: 49
## initial value 39496.064346
## final value 36921.822250
## converged
## # weights: 49
## initial value 38944.691421
## iter 10 value 36930.407630
## iter 20 value 36922.425705
## iter 30 value 36922.320463
## final value 36922.315383
## converged
## # weights: 49
## initial value 38917.741448
## iter 10 value 36928.312307
## iter 20 value 36925.374756
## iter 20 value 36925.374616
## iter 20 value 36925.374597
## final value 36925.374597
## converged
## # weights: 61
## initial value 39022.282939
## final value 36921.822250
## converged
## # weights: 61
## initial value 39568.582001
## iter 10 value 36986.232733
## iter 20 value 36924.216157
## iter 30 value 36922.472683
## iter 40 value 36922.282327
## final value 36922.276264
## converged
## # weights: 61
## initial value 39447.091785
## iter 10 value 36944.586325
## iter 20 value 36925.116741
## final value 36925.095545
## converged
## # weights: 73
## initial value 39875.620702
## final value 36921.822250
## converged
## # weights: 73
## initial value 39216.990123
## iter 10 value 36988.018064
## iter 20 value 36923.960624
## iter 30 value 36922.318907
## iter 40 value 36922.245421
## iter 40 value 36922.245102
## iter 40 value 36922.244964
## final value 36922.244964
## converged
## # weights: 73
## initial value 39412.976265
## iter 10 value 36945.616937
## iter 20 value 36924.878311
## final value 36924.872487
## converged
## # weights: 85
## initial value 40196.341367
## final value 36921.822250
## converged
## # weights: 85
## initial value 39856.112170
## iter 10 value 36933.528863
## iter 20 value 36922.380453
## iter 30 value 36922.221408
## final value 36922.219714
## converged
## # weights: 85
## initial value 39234.250660
## iter 10 value 36951.671636
## iter 20 value 36924.692658
## final value 36924.687312
## converged
## # weights: 97
## initial value 39467.974074
## final value 36921.822250
## converged
## # weights: 97
## initial value 40472.542360
## iter 10 value 36934.597538
## iter 20 value 36922.414276
## iter 30 value 36922.202693
## final value 36922.197258
## converged
## # weights: 97
## initial value 39956.061191
## iter 10 value 36955.306156
## iter 20 value 36924.533152
## final value 36924.529235
## converged
## # weights: 109
## initial value 40248.867065
## final value 36921.822250
## converged
## # weights: 109
## initial value 38917.557639
## iter 10 value 37001.501481
## iter 20 value 36924.375518
## iter 30 value 36922.386249
## iter 40 value 36922.182228
## final value 36922.177823
## converged
## # weights: 109
## initial value 39347.612475
## iter 10 value 36956.085771
## iter 20 value 36924.403878
## final value 36924.391630
## converged
## # weights: 121
## initial value 39379.438706
## final value 36921.822250
## converged
## # weights: 121
## initial value 37482.709180
## iter 10 value 36926.628809
## iter 20 value 36922.213164
## final value 36922.161983
## converged
## # weights: 121
## initial value 40267.319435
## iter 10 value 36956.147880
## iter 20 value 36924.276785
## final value 36924.270096
## converged
## # weights: 13
## initial value 39393.380536
## final value 36842.470143
## converged
## # weights: 13
## initial value 38721.655172
## iter 10 value 36875.717944
## iter 20 value 36844.190444
## iter 30 value 36843.332867
## iter 40 value 36843.258085
## iter 40 value 36843.257732
## iter 40 value 36843.257589
## final value 36843.257589
## converged
## # weights: 13
## initial value 39712.751137
## iter 10 value 36849.124506
## final value 36847.907476
## converged
## # weights: 25
## initial value 39030.927217
## final value 36842.470143
## converged
## # weights: 25
## initial value 39513.836856
## iter 10 value 36881.695289
## iter 20 value 36843.749069
## iter 30 value 36843.136662
## iter 40 value 36843.103073
## iter 40 value 36843.102860
## iter 40 value 36843.102819
## final value 36843.102819
## converged
## # weights: 25
## initial value 38987.577841
## iter 10 value 36847.954270
## final value 36846.941548
## converged
## # weights: 37
## initial value 39305.895512
## final value 36842.470143
## converged
## # weights: 37
## initial value 40436.068662
## iter 10 value 36876.235888
## iter 20 value 36844.281803
## iter 30 value 36843.057389
## final value 36843.018741
## converged
## # weights: 37
## initial value 40406.990372
## iter 10 value 36850.216878
## iter 20 value 36846.395435
## iter 20 value 36846.395068
## iter 20 value 36846.395055
## final value 36846.395055
## converged
## # weights: 49
## initial value 39974.016726
## final value 36842.470143
## converged
## # weights: 49
## initial value 39342.909995
## iter 10 value 36905.111885
## iter 20 value 36844.281953
## iter 30 value 36843.043037
## final value 36842.964971
## converged
## # weights: 49
## initial value 39385.862647
## iter 10 value 36858.979257
## iter 20 value 36846.031307
## final value 36846.023541
## converged
## # weights: 61
## initial value 39656.468287
## final value 36842.470143
## converged
## # weights: 61
## initial value 38903.649087
## iter 10 value 36899.614261
## iter 20 value 36844.254828
## iter 30 value 36842.997738
## iter 40 value 36842.925640
## final value 36842.924192
## converged
## # weights: 61
## initial value 38466.938365
## iter 10 value 36861.249952
## iter 20 value 36845.758135
## final value 36845.744278
## converged
## # weights: 73
## initial value 39393.773135
## final value 36842.470143
## converged
## # weights: 73
## initial value 39874.770529
## iter 10 value 36857.299733
## iter 20 value 36843.199804
## iter 30 value 36842.905584
## final value 36842.892833
## converged
## # weights: 73
## initial value 38322.042701
## iter 10 value 36864.119178
## iter 20 value 36845.523706
## final value 36845.521341
## converged
## # weights: 85
## initial value 39701.969949
## final value 36842.470143
## converged
## # weights: 85
## initial value 38323.943873
## iter 10 value 36894.662395
## iter 20 value 36844.374894
## iter 30 value 36842.916994
## iter 40 value 36842.868857
## final value 36842.866541
## converged
## # weights: 85
## initial value 39489.890917
## iter 10 value 36855.307365
## iter 20 value 36845.337110
## final value 36845.336029
## converged
## # weights: 97
## initial value 39030.502465
## final value 36842.470143
## converged
## # weights: 97
## initial value 40042.463409
## iter 10 value 36855.040131
## iter 20 value 36843.090346
## iter 30 value 36842.852310
## final value 36842.844162
## converged
## # weights: 97
## initial value 40371.127948
## iter 10 value 36869.573932
## iter 20 value 36845.180757
## final value 36845.177982
## converged
## # weights: 109
## initial value 39378.479280
## final value 36842.470143
## converged
## # weights: 109
## initial value 38388.667446
## iter 10 value 36846.995291
## iter 20 value 36842.861859
## final value 36842.825975
## converged
## # weights: 109
## initial value 38966.758788
## iter 10 value 36875.833006
## iter 20 value 36845.044734
## final value 36845.040305
## converged
## # weights: 121
## initial value 39812.713283
## final value 36842.470143
## converged
## # weights: 121
## initial value 38904.981965
## iter 10 value 36848.437001
## iter 20 value 36842.818053
## final value 36842.809804
## converged
## # weights: 121
## initial value 39736.255220
## iter 10 value 36880.384656
## iter 20 value 36844.923901
## final value 36844.918704
## converged
## # weights: 13
## initial value 39237.783407
## final value 36404.974112
## converged
## # weights: 13
## initial value 38260.262244
## iter 10 value 36432.846542
## iter 20 value 36406.198678
## iter 30 value 36405.779836
## final value 36405.760308
## converged
## # weights: 13
## initial value 38651.662597
## iter 10 value 36411.570058
## final value 36410.404333
## converged
## # weights: 25
## initial value 38905.134809
## final value 36404.974112
## converged
## # weights: 25
## initial value 37714.963922
## iter 10 value 36431.509914
## iter 20 value 36406.369854
## iter 30 value 36405.642614
## final value 36405.606198
## converged
## # weights: 25
## initial value 39794.503962
## iter 10 value 36410.383879
## iter 20 value 36409.440093
## final value 36409.439489
## converged
## # weights: 37
## initial value 39822.735656
## final value 36404.974112
## converged
## # weights: 37
## initial value 38406.762979
## iter 10 value 36450.749429
## iter 20 value 36406.721329
## iter 30 value 36405.588401
## iter 40 value 36405.524766
## final value 36405.522011
## converged
## # weights: 37
## initial value 40062.164770
## iter 10 value 36418.363928
## iter 20 value 36408.894727
## final value 36408.894016
## converged
## # weights: 49
## initial value 38155.799106
## final value 36404.974112
## converged
## # weights: 49
## initial value 37497.447702
## iter 10 value 36433.926057
## iter 20 value 36406.613595
## iter 30 value 36405.554179
## iter 40 value 36405.469185
## final value 36405.468055
## converged
## # weights: 49
## initial value 39991.814767
## iter 10 value 36420.141958
## iter 20 value 36408.546370
## final value 36408.522954
## converged
## # weights: 61
## initial value 39087.209599
## final value 36404.974112
## converged
## # weights: 61
## initial value 38136.672286
## iter 10 value 36459.801311
## iter 20 value 36406.943011
## iter 30 value 36405.524924
## iter 40 value 36405.431171
## final value 36405.428448
## converged
## # weights: 61
## initial value 38805.791135
## iter 10 value 36409.685346
## final value 36408.244080
## converged
## # weights: 73
## initial value 39106.238917
## final value 36404.974112
## converged
## # weights: 73
## initial value 38628.584525
## iter 10 value 36420.495139
## iter 20 value 36405.616714
## iter 30 value 36405.401263
## final value 36405.394881
## converged
## # weights: 73
## initial value 38837.405690
## iter 10 value 36427.640065
## iter 20 value 36408.023828
## final value 36408.021175
## converged
## # weights: 85
## initial value 38253.221643
## final value 36404.974112
## converged
## # weights: 85
## initial value 39803.452251
## iter 10 value 36465.590443
## iter 20 value 36407.209423
## iter 30 value 36405.489207
## iter 40 value 36405.374282
## final value 36405.370074
## converged
## # weights: 85
## initial value 40217.725660
## iter 10 value 36452.526669
## iter 20 value 36408.265487
## final value 36407.836226
## converged
## # weights: 97
## initial value 40276.537277
## final value 36404.974112
## converged
## # weights: 97
## initial value 38139.156633
## iter 10 value 36469.582673
## iter 20 value 36407.102804
## iter 30 value 36405.427176
## iter 40 value 36405.351238
## final value 36405.347766
## converged
## # weights: 97
## initial value 37882.327704
## iter 10 value 36434.228221
## iter 20 value 36407.684759
## final value 36407.678356
## converged
## # weights: 109
## initial value 39566.020842
## final value 36404.974112
## converged
## # weights: 109
## initial value 38872.484524
## iter 10 value 36501.043147
## iter 20 value 36407.601215
## iter 30 value 36405.535121
## iter 40 value 36405.335225
## final value 36405.329622
## converged
## # weights: 109
## initial value 38865.177266
## iter 10 value 36441.118972
## iter 20 value 36407.549645
## final value 36407.540972
## converged
## # weights: 121
## initial value 37595.512927
## final value 36404.974112
## converged
## # weights: 121
## initial value 40173.377276
## iter 10 value 36422.572454
## iter 20 value 36405.933243
## iter 30 value 36405.318671
## final value 36405.312924
## converged
## # weights: 121
## initial value 40267.765094
## iter 10 value 36409.147788
## iter 20 value 36407.420273
## iter 20 value 36407.419942
## iter 20 value 36407.419632
## final value 36407.419632
## converged
## # weights: 13
## initial value 39936.802150
## final value 36601.713943
## converged
## # weights: 13
## initial value 38557.020658
## iter 10 value 36634.614965
## iter 20 value 36603.189760
## iter 30 value 36602.531377
## final value 36602.500361
## converged
## # weights: 13
## initial value 38666.526969
## iter 10 value 36607.627473
## final value 36607.146912
## converged
## # weights: 25
## initial value 38390.746242
## final value 36601.713943
## converged
## # weights: 25
## initial value 38490.779703
## iter 10 value 36638.490732
## iter 20 value 36603.391040
## iter 30 value 36602.378064
## final value 36602.346246
## converged
## # weights: 25
## initial value 39169.972116
## iter 10 value 36607.937448
## final value 36606.181563
## converged
## # weights: 37
## initial value 39398.214382
## final value 36601.713943
## converged
## # weights: 37
## initial value 39382.462206
## iter 10 value 36649.350423
## iter 20 value 36603.414065
## iter 30 value 36602.326082
## iter 40 value 36602.263875
## iter 40 value 36602.263531
## iter 40 value 36602.263386
## final value 36602.263386
## converged
## # weights: 37
## initial value 38155.745788
## iter 10 value 36609.200256
## iter 20 value 36605.635927
## iter 20 value 36605.635702
## iter 20 value 36605.635696
## final value 36605.635696
## converged
## # weights: 49
## initial value 39644.159141
## final value 36601.713943
## converged
## # weights: 49
## initial value 37800.283261
## iter 10 value 36634.469536
## iter 20 value 36603.490611
## iter 30 value 36602.270960
## iter 40 value 36602.208736
## iter 40 value 36602.208455
## iter 40 value 36602.208303
## final value 36602.208303
## converged
## # weights: 49
## initial value 38547.592865
## iter 10 value 36620.469228
## iter 20 value 36605.265044
## final value 36605.264434
## converged
## # weights: 61
## initial value 38808.850907
## final value 36601.713943
## converged
## # weights: 61
## initial value 39272.479005
## iter 10 value 36664.567941
## iter 20 value 36603.914497
## iter 30 value 36602.348960
## iter 40 value 36602.172095
## final value 36602.167499
## converged
## # weights: 61
## initial value 38736.680640
## iter 10 value 36620.840199
## iter 20 value 36604.991916
## final value 36604.985428
## converged
## # weights: 73
## initial value 40218.724662
## final value 36601.713943
## converged
## # weights: 73
## initial value 38255.775300
## iter 10 value 36653.069284
## iter 20 value 36603.670370
## iter 30 value 36602.205053
## iter 40 value 36602.138701
## final value 36602.136367
## converged
## # weights: 73
## initial value 38667.118184
## iter 10 value 36626.124025
## iter 20 value 36604.764601
## final value 36604.762547
## converged
## # weights: 85
## initial value 39129.829182
## final value 36601.713943
## converged
## # weights: 85
## initial value 39134.415060
## iter 10 value 36674.641717
## iter 20 value 36603.663480
## iter 30 value 36602.201500
## iter 40 value 36602.113084
## final value 36602.109808
## converged
## # weights: 85
## initial value 37857.988480
## iter 10 value 36624.787206
## iter 20 value 36604.579860
## final value 36604.577520
## converged
## # weights: 97
## initial value 38792.714322
## final value 36601.713943
## converged
## # weights: 97
## initial value 39336.997294
## iter 10 value 36610.398499
## iter 20 value 36602.200308
## iter 30 value 36602.089990
## final value 36602.088962
## converged
## # weights: 97
## initial value 39811.078628
## iter 10 value 36631.761728
## iter 20 value 36604.424357
## final value 36604.419494
## converged
## # weights: 109
## initial value 38922.075554
## final value 36601.713943
## converged
## # weights: 109
## initial value 39177.743833
## iter 10 value 36699.333388
## iter 20 value 36604.250663
## iter 30 value 36602.318294
## iter 40 value 36602.075579
## final value 36602.069700
## converged
## # weights: 109
## initial value 39917.499212
## iter 10 value 36636.273520
## iter 20 value 36604.286190
## final value 36604.282044
## converged
## # weights: 121
## initial value 38414.331140
## final value 36601.713943
## converged
## # weights: 121
## initial value 39265.765566
## iter 10 value 36614.583580
## iter 20 value 36603.633543
## iter 30 value 36602.110515
## final value 36602.053011
## converged
## # weights: 121
## initial value 38657.018288
## iter 10 value 36645.627278
## iter 20 value 36604.168121
## final value 36604.160489
## converged
## # weights: 13
## initial value 38495.677449
## final value 36857.577565
## converged
## # weights: 13
## initial value 38760.771847
## iter 10 value 36885.734399
## iter 20 value 36858.787697
## iter 30 value 36858.373125
## final value 36858.365342
## converged
## # weights: 13
## initial value 39265.617283
## iter 10 value 36863.414091
## final value 36863.015019
## converged
## # weights: 25
## initial value 39370.415853
## final value 36857.577565
## converged
## # weights: 25
## initial value 39382.307240
## iter 10 value 36897.944057
## iter 20 value 36858.871520
## iter 30 value 36858.248730
## final value 36858.210107
## converged
## # weights: 25
## initial value 39453.841179
## iter 10 value 36863.661474
## final value 36862.049003
## converged
## # weights: 37
## initial value 38809.758383
## final value 36857.577565
## converged
## # weights: 37
## initial value 40286.346134
## iter 10 value 36895.852494
## iter 20 value 36859.299183
## iter 30 value 36858.272305
## iter 40 value 36858.134987
## final value 36858.127061
## converged
## # weights: 37
## initial value 39659.718272
## iter 10 value 36864.982961
## iter 20 value 36861.502457
## iter 20 value 36861.502310
## iter 20 value 36861.502303
## final value 36861.502303
## converged
## # weights: 49
## initial value 39872.212944
## final value 36857.577565
## converged
## # weights: 49
## initial value 38970.308503
## iter 10 value 36913.110882
## iter 20 value 36859.470189
## iter 30 value 36858.165638
## iter 40 value 36858.075135
## final value 36858.072050
## converged
## # weights: 49
## initial value 38486.394291
## iter 10 value 36863.174479
## final value 36861.130817
## converged
## # weights: 61
## initial value 38517.594114
## final value 36857.577565
## converged
## # weights: 61
## initial value 39876.772536
## iter 10 value 36909.354416
## iter 20 value 36859.187469
## iter 30 value 36858.149816
## iter 40 value 36858.033766
## final value 36858.031165
## converged
## # weights: 61
## initial value 40134.629245
## iter 10 value 36878.941828
## iter 20 value 36860.851830
## iter 20 value 36860.851657
## iter 20 value 36860.851653
## final value 36860.851653
## converged
## # weights: 73
## initial value 40760.453584
## final value 36857.577565
## converged
## # weights: 73
## initial value 39460.748899
## iter 10 value 36931.642973
## iter 20 value 36859.895590
## iter 30 value 36858.192728
## iter 40 value 36858.004216
## final value 36857.999995
## converged
## # weights: 73
## initial value 39634.962752
## iter 10 value 36882.124641
## iter 20 value 36860.631686
## final value 36860.628528
## converged
## # weights: 85
## initial value 38437.836466
## final value 36857.577565
## converged
## # weights: 85
## initial value 39440.795593
## iter 10 value 36918.522748
## iter 20 value 36859.346774
## iter 30 value 36858.005092
## final value 36857.975045
## converged
## # weights: 85
## initial value 39082.251259
## iter 10 value 36883.538628
## iter 20 value 36860.446628
## final value 36860.443325
## converged
## # weights: 97
## initial value 39747.260599
## final value 36857.577565
## converged
## # weights: 97
## initial value 39143.932805
## iter 10 value 36938.864387
## iter 20 value 36859.801375
## iter 30 value 36858.133395
## iter 40 value 36857.958648
## final value 36857.953351
## converged
## # weights: 97
## initial value 38384.095071
## iter 10 value 36884.562598
## iter 20 value 36860.287707
## final value 36860.285256
## converged
## # weights: 109
## initial value 39929.184304
## final value 36857.577565
## converged
## # weights: 109
## initial value 38098.210645
## iter 10 value 36864.668514
## iter 20 value 36858.231932
## iter 30 value 36857.949191
## final value 36857.933213
## converged
## # weights: 109
## initial value 39247.871848
## iter 10 value 36894.963479
## iter 20 value 36860.153580
## final value 36860.147558
## converged
## # weights: 121
## initial value 40181.388028
## final value 36857.577565
## converged
## # weights: 121
## initial value 39844.378354
## iter 10 value 36876.097287
## iter 20 value 36858.223478
## iter 30 value 36857.919216
## final value 36857.916402
## converged
## # weights: 121
## initial value 38739.633475
## iter 10 value 36895.836410
## iter 20 value 36860.029197
## final value 36860.026037
## converged
## # weights: 13
## initial value 39949.402928
## final value 37151.229854
## converged
## # weights: 13
## initial value 40383.055183
## iter 10 value 37177.684722
## iter 20 value 37152.392182
## iter 30 value 37152.040521
## final value 37152.017079
## converged
## # weights: 13
## initial value 39273.521630
## iter 10 value 37157.301745
## final value 37156.670753
## converged
## # weights: 25
## initial value 40365.486484
## final value 37151.229854
## converged
## # weights: 25
## initial value 39675.908745
## iter 10 value 37192.099909
## iter 20 value 37152.910409
## iter 30 value 37151.898309
## iter 40 value 37151.863291
## final value 37151.862563
## converged
## # weights: 25
## initial value 40629.800739
## iter 10 value 37157.302521
## iter 20 value 37155.706841
## final value 37155.703796
## converged
## # weights: 37
## initial value 38441.747209
## final value 37151.229854
## converged
## # weights: 37
## initial value 39986.462062
## iter 10 value 37198.637580
## iter 20 value 37152.895312
## iter 30 value 37151.837433
## final value 37151.779062
## converged
## # weights: 37
## initial value 40236.121144
## iter 10 value 37158.238166
## iter 20 value 37155.160905
## final value 37155.157063
## converged
## # weights: 49
## initial value 40840.989642
## final value 37151.229854
## converged
## # weights: 49
## initial value 39376.350516
## iter 10 value 37207.846311
## iter 20 value 37152.975767
## iter 30 value 37151.810562
## iter 40 value 37151.725810
## iter 40 value 37151.725525
## iter 40 value 37151.725345
## final value 37151.725345
## converged
## # weights: 49
## initial value 39247.756102
## iter 10 value 37163.008738
## iter 20 value 37154.785620
## final value 37154.785134
## converged
## # weights: 61
## initial value 40042.359916
## final value 37151.229854
## converged
## # weights: 61
## initial value 40457.241270
## iter 10 value 37210.234862
## iter 20 value 37153.278400
## iter 30 value 37151.859079
## iter 40 value 37151.689883
## final value 37151.684204
## converged
## # weights: 61
## initial value 38485.866701
## iter 10 value 37169.782662
## iter 20 value 37154.508828
## final value 37154.505690
## converged
## # weights: 73
## initial value 40359.247817
## final value 37151.229854
## converged
## # weights: 73
## initial value 38583.778555
## iter 10 value 37197.159862
## iter 20 value 37153.184807
## iter 30 value 37151.754479
## iter 40 value 37151.656086
## final value 37151.652250
## converged
## # weights: 73
## initial value 38567.729744
## iter 10 value 37170.994352
## iter 20 value 37154.285303
## final value 37154.282562
## converged
## # weights: 85
## initial value 40737.889252
## final value 37151.229854
## converged
## # weights: 85
## initial value 40157.646916
## iter 10 value 37164.312657
## iter 20 value 37151.714425
## iter 30 value 37151.627686
## iter 30 value 37151.627395
## iter 30 value 37151.627240
## final value 37151.627240
## converged
## # weights: 85
## initial value 39621.128259
## iter 10 value 37178.134627
## iter 20 value 37154.104704
## final value 37154.097266
## converged
## # weights: 97
## initial value 38425.027925
## final value 37151.229854
## converged
## # weights: 97
## initial value 38177.226286
## iter 10 value 37187.563860
## iter 20 value 37153.278262
## iter 30 value 37151.691547
## iter 40 value 37151.608449
## final value 37151.604419
## converged
## # weights: 97
## initial value 40284.323310
## iter 10 value 37185.112186
## iter 20 value 37153.943924
## final value 37153.939055
## converged
## # weights: 109
## initial value 39939.583387
## final value 37151.229854
## converged
## # weights: 109
## initial value 40863.848635
## iter 10 value 37208.880904
## iter 20 value 37153.566159
## iter 30 value 37151.729183
## iter 40 value 37151.592869
## final value 37151.586026
## converged
## # weights: 109
## initial value 38615.914852
## iter 10 value 37167.878254
## iter 20 value 37153.813347
## final value 37153.801253
## converged
## # weights: 121
## initial value 40032.162485
## final value 37151.229854
## converged
## # weights: 121
## initial value 38593.936700
## iter 10 value 37151.687887
## iter 20 value 37151.569851
## iter 20 value 37151.569625
## iter 20 value 37151.569532
## final value 37151.569532
## converged
## # weights: 121
## initial value 38799.534316
## iter 10 value 37191.032611
## iter 20 value 37153.684440
## final value 37153.679689
## converged
## Warning in nominalTrainWorkflow(x = x, y = y, wts = weights, info =
## trainInfo, : There were missing values in resampled performance measures.
## # weights: 13
## initial value 43851.512535
## final value 40875.712287
## converged
## RMSE Rsquared MAE
## 14.27693 NA 13.38691
3] Support Vector Machine -
perfsvm = model.eval('svmRadial')
## RMSE Rsquared MAE
## 2.2552633 0.7994934 1.7222081
4] Multivariate Adaptive Regression Splines -
marsGrid = expand.grid(degree = 1:2, nprune = 2:38)
perfmars = model.eval('earth', marsGrid)
## RMSE Rsquared MAE
## 1.3061003 0.9308395 1.0385604
df.perf = rbind(data.frame(Name = 'KNN', RMSE = perfknn[1]), data.frame(Name= 'NN', RMSE = perfnn[1]) , data.frame(Name = 'SVM', RMSE = perfsvm[1]), data.frame(Name = 'MARS', RMSE = perfmars[1]))
ggplot() +
geom_bar(data = df.perf, aes(x = Name, y = RMSE, fill=Name), stat="identity")
7.5
Prepare Data
library(AppliedPredictiveModeling)
## Warning: package 'AppliedPredictiveModeling' was built under R version
## 3.6.3
data(ChemicalManufacturingProcess)
tmp.data <- mice(ChemicalManufacturingProcess,m=2,maxit=5,meth='pmm',seed=500)
##
## iter imp variable
## 1 1 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 1 2 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 2 1 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 2 2 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 3 1 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 3 2 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 4 1 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 4 2 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 5 1 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## 5 2 ManufacturingProcess01 ManufacturingProcess02 ManufacturingProcess03 ManufacturingProcess04 ManufacturingProcess05 ManufacturingProcess06 ManufacturingProcess07 ManufacturingProcess08 ManufacturingProcess10 ManufacturingProcess11 ManufacturingProcess12 ManufacturingProcess14 ManufacturingProcess22 ManufacturingProcess23 ManufacturingProcess24 ManufacturingProcess25 ManufacturingProcess26 ManufacturingProcess27 ManufacturingProcess28 ManufacturingProcess29 ManufacturingProcess30 ManufacturingProcess31 ManufacturingProcess33 ManufacturingProcess34 ManufacturingProcess35 ManufacturingProcess36 ManufacturingProcess40 ManufacturingProcess41
## Warning: Number of logged events: 270
ChemicalManufacturingProcess = complete(tmp.data)
# train test split
set.seed(100)
rows = nrow(ChemicalManufacturingProcess)
t.index <- sample(1:rows, size = round(0.75*rows), replace=FALSE)
df.train <- ChemicalManufacturingProcess[t.index ,]
df.test <- ChemicalManufacturingProcess[-t.index ,]
df.train.x = df.train[,-1]
df.train.y = df.train[,1]
df.test.x = df.test[,-1]
df.test.y = df.test[,1]
model.eval = function(modelmethod, gridSearch = NULL)
{
Model = train(x = df.train.x, y = df.train.y, method = modelmethod, tuneGrid = gridSearch, preProcess = c('center', 'scale'), trControl = trainControl(method='cv'))
Pred = predict(Model, newdata = df.test.x)
modelperf = postResample(Pred, df.test.y)
print(modelperf)
}
1] K-Nearest Neighbors -
perfknn = model.eval('knn')
## RMSE Rsquared MAE
## 1.2451733 0.4023846 0.9605909
2] Neural Net -
nnetGrid = expand.grid(decay = c(0,0.01, .1), size = c(1:10))
perfnn = model.eval('nnet', nnetGrid)
## # weights: 60
## initial value 185588.808401
## final value 181452.963300
## converged
## # weights: 60
## initial value 185975.388644
## iter 10 value 181566.256724
## iter 20 value 181455.328421
## iter 30 value 181454.133784
## iter 40 value 181453.857831
## final value 181453.831278
## converged
## # weights: 60
## initial value 185918.975766
## iter 10 value 181464.066211
## iter 20 value 181460.545743
## final value 181459.052351
## converged
## # weights: 119
## initial value 186942.251861
## final value 181452.963300
## converged
## # weights: 119
## initial value 188004.865688
## iter 10 value 181550.154446
## iter 20 value 181455.876870
## iter 30 value 181453.997837
## iter 40 value 181453.668681
## final value 181453.657773
## converged
## # weights: 119
## initial value 186031.359242
## iter 10 value 181493.057876
## iter 20 value 181458.313467
## final value 181457.942272
## converged
## # weights: 178
## initial value 185913.099115
## final value 181452.963300
## converged
## # weights: 178
## initial value 186556.448826
## iter 10 value 181511.143643
## iter 20 value 181455.182983
## iter 30 value 181453.934965
## iter 40 value 181453.606353
## final value 181453.564285
## converged
## # weights: 178
## initial value 187668.816204
## iter 10 value 181510.933856
## iter 20 value 181458.235446
## final value 181457.322202
## converged
## # weights: 237
## initial value 185075.279526
## final value 181452.963300
## converged
## # weights: 237
## initial value 185575.536037
## iter 10 value 181509.883656
## iter 20 value 181455.925195
## iter 30 value 181453.782832
## iter 40 value 181453.528055
## final value 181453.504211
## converged
## # weights: 237
## initial value 188006.774896
## iter 10 value 181460.504584
## iter 20 value 181456.971254
## final value 181456.903648
## converged
## # weights: 296
## initial value 186479.639067
## final value 181452.963300
## converged
## # weights: 296
## initial value 183799.634110
## iter 10 value 181455.490383
## iter 20 value 181453.494348
## final value 181453.460403
## converged
## # weights: 296
## initial value 186517.581791
## iter 10 value 181545.405174
## iter 20 value 181457.932203
## iter 30 value 181456.596056
## final value 181456.590723
## converged
## # weights: 355
## initial value 186944.591817
## final value 181452.963300
## converged
## # weights: 355
## initial value 186291.075839
## iter 10 value 181454.228419
## iter 20 value 181453.479922
## final value 181453.429364
## converged
## # weights: 355
## initial value 185340.948354
## iter 10 value 181463.568274
## iter 20 value 181456.585202
## final value 181456.342995
## converged
## # weights: 414
## initial value 186576.571360
## final value 181452.963300
## converged
## # weights: 414
## initial value 185924.482868
## iter 10 value 181453.613348
## iter 20 value 181453.411009
## final value 181453.397570
## converged
## # weights: 414
## initial value 186228.472230
## iter 10 value 181464.563054
## iter 20 value 181456.154017
## final value 181456.137414
## converged
## # weights: 473
## initial value 188380.782906
## final value 181452.963300
## converged
## # weights: 473
## initial value 188782.770816
## iter 10 value 181473.423392
## iter 20 value 181453.886765
## iter 30 value 181453.403239
## final value 181453.376579
## converged
## # weights: 473
## initial value 184534.979133
## iter 10 value 181458.417497
## iter 20 value 181455.969314
## final value 181455.963647
## converged
## # weights: 532
## initial value 183223.418462
## final value 181452.963300
## converged
## # weights: 532
## initial value 185339.830765
## iter 10 value 181453.478129
## final value 181453.354668
## converged
## # weights: 532
## initial value 186331.703308
## iter 10 value 181459.287650
## iter 20 value 181455.859370
## final value 181455.810168
## converged
## # weights: 591
## initial value 187089.797503
## final value 181452.963300
## converged
## # weights: 591
## initial value 185969.780808
## iter 10 value 181453.669710
## iter 20 value 181453.339501
## final value 181453.336347
## converged
## # weights: 591
## initial value 186434.145650
## iter 10 value 181473.504315
## iter 20 value 181455.688028
## final value 181455.676568
## converged
## # weights: 60
## initial value 185314.290667
## final value 181255.535600
## converged
## # weights: 60
## initial value 186948.740806
## iter 10 value 181368.770731
## iter 20 value 181257.969354
## iter 30 value 181256.690788
## iter 40 value 181256.422899
## final value 181256.403641
## converged
## # weights: 60
## initial value 185755.160108
## iter 10 value 181263.807026
## final value 181261.625711
## converged
## # weights: 119
## initial value 185606.164643
## final value 181255.535600
## converged
## # weights: 119
## initial value 186050.663054
## iter 10 value 181272.546822
## iter 20 value 181256.446975
## iter 30 value 181256.300938
## iter 40 value 181256.233448
## final value 181256.229927
## converged
## # weights: 119
## initial value 184320.064067
## iter 10 value 181298.050917
## iter 20 value 181261.280474
## iter 30 value 181260.515966
## iter 30 value 181260.514728
## iter 30 value 181260.514712
## final value 181260.514712
## converged
## # weights: 178
## initial value 183304.505170
## final value 181255.535600
## converged
## # weights: 178
## initial value 186261.288720
## iter 10 value 181303.988865
## iter 20 value 181260.588353
## iter 30 value 181256.429074
## iter 40 value 181256.170076
## final value 181256.143652
## converged
## # weights: 178
## initial value 186045.297869
## iter 10 value 181315.115389
## iter 20 value 181260.417017
## iter 30 value 181259.895502
## iter 30 value 181259.894050
## iter 30 value 181259.894019
## final value 181259.894019
## converged
## # weights: 237
## initial value 186803.599505
## final value 181255.535600
## converged
## # weights: 237
## initial value 184837.779127
## iter 10 value 181257.215201
## iter 20 value 181256.203055
## iter 30 value 181256.094838
## final value 181256.077129
## converged
## # weights: 237
## initial value 186922.187191
## iter 10 value 181332.079370
## iter 20 value 181260.652521
## iter 30 value 181259.476236
## iter 30 value 181259.475319
## iter 30 value 181259.475319
## final value 181259.475319
## converged
## # weights: 296
## initial value 187607.627420
## final value 181255.535600
## converged
## # weights: 296
## initial value 186543.113678
## iter 10 value 181282.896170
## iter 20 value 181257.134576
## iter 30 value 181256.220515
## iter 40 value 181256.062337
## final value 181256.034353
## converged
## # weights: 296
## initial value 187088.694563
## iter 10 value 181346.866681
## iter 20 value 181260.555047
## iter 30 value 181259.172336
## iter 30 value 181259.171006
## iter 30 value 181259.170967
## final value 181259.170967
## converged
## # weights: 355
## initial value 184826.215264
## final value 181255.535600
## converged
## # weights: 355
## initial value 184742.104936
## iter 10 value 181256.712651
## iter 20 value 181256.042885
## final value 181255.998055
## converged
## # weights: 355
## initial value 185313.462197
## iter 10 value 181270.711227
## iter 20 value 181260.285682
## iter 30 value 181258.918508
## final value 181258.915021
## converged
## # weights: 414
## initial value 186720.529923
## final value 181255.535600
## converged
## # weights: 414
## initial value 185378.888363
## iter 10 value 181256.634237
## iter 20 value 181255.998210
## final value 181255.971308
## converged
## # weights: 414
## initial value 186177.564973
## iter 10 value 181264.353498
## iter 20 value 181258.716910
## final value 181258.709070
## converged
## # weights: 473
## initial value 188073.018768
## final value 181255.535600
## converged
## # weights: 473
## initial value 185010.816446
## iter 10 value 181256.103426
## iter 20 value 181255.949713
## iter 20 value 181255.948472
## iter 20 value 181255.947890
## final value 181255.947890
## converged
## # weights: 473
## initial value 187588.703950
## iter 10 value 181260.661902
## iter 20 value 181258.556706
## final value 181258.534744
## converged
## # weights: 532
## initial value 189059.593746
## final value 181255.535600
## converged
## # weights: 532
## initial value 185910.999088
## iter 10 value 181256.212258
## final value 181255.927204
## converged
## # weights: 532
## initial value 184918.637745
## iter 10 value 181262.176514
## iter 20 value 181258.415623
## final value 181258.382021
## converged
## # weights: 591
## initial value 183648.857517
## final value 181255.535600
## converged
## # weights: 591
## initial value 186397.270981
## iter 10 value 181256.445526
## iter 20 value 181255.909567
## iter 20 value 181255.908661
## iter 20 value 181255.908243
## final value 181255.908243
## converged
## # weights: 591
## initial value 186320.702898
## iter 10 value 181265.965200
## iter 20 value 181259.213531
## iter 30 value 181258.249540
## iter 30 value 181258.248238
## iter 30 value 181258.248156
## final value 181258.248156
## converged
## # weights: 60
## initial value 188179.895588
## final value 182375.451100
## converged
## # weights: 60
## initial value 187731.220503
## iter 10 value 182493.655161
## iter 20 value 182377.797108
## iter 30 value 182376.634368
## iter 40 value 182376.321216
## iter 40 value 182376.320220
## iter 40 value 182376.319725
## final value 182376.319725
## converged
## # weights: 60
## initial value 186730.486393
## iter 10 value 182385.406599
## iter 20 value 182381.590267
## final value 182381.546843
## converged
## # weights: 119
## initial value 188435.942820
## final value 182375.451100
## converged
## # weights: 119
## initial value 188029.613000
## iter 10 value 182394.426312
## iter 20 value 182376.703934
## iter 30 value 182376.336611
## iter 40 value 182376.205990
## final value 182376.148168
## converged
## # weights: 119
## initial value 188061.736999
## iter 10 value 182418.487129
## iter 20 value 182381.001890
## final value 182380.435122
## converged
## # weights: 178
## initial value 188420.006854
## final value 182375.451100
## converged
## # weights: 178
## initial value 185408.029210
## iter 10 value 182419.193614
## iter 20 value 182376.781613
## iter 30 value 182376.147859
## iter 40 value 182376.070916
## final value 182376.064325
## converged
## # weights: 178
## initial value 185823.762552
## iter 10 value 182434.185565
## iter 20 value 182380.612664
## iter 30 value 182379.818324
## final value 182379.814223
## converged
## # weights: 237
## initial value 187655.925049
## final value 182375.451100
## converged
## # weights: 237
## initial value 185338.145500
## iter 10 value 182376.335651
## iter 20 value 182376.005135
## iter 20 value 182376.003322
## iter 20 value 182376.002030
## final value 182376.002030
## converged
## # weights: 237
## initial value 187046.621504
## iter 10 value 182454.595968
## iter 20 value 182379.915193
## iter 30 value 182379.396316
## iter 30 value 182379.395019
## iter 30 value 182379.394951
## final value 182379.394951
## converged
## # weights: 296
## initial value 188065.472343
## final value 182375.451100
## converged
## # weights: 296
## initial value 187487.110544
## iter 10 value 182405.773783
## iter 20 value 182376.205052
## iter 30 value 182375.962195
## final value 182375.953412
## converged
## # weights: 296
## initial value 187348.577447
## iter 10 value 182465.061430
## iter 20 value 182380.335376
## iter 30 value 182379.101063
## iter 30 value 182379.099321
## iter 30 value 182379.099274
## final value 182379.099274
## converged
## # weights: 355
## initial value 189790.098528
## final value 182375.451100
## converged
## # weights: 355
## initial value 186418.550647
## iter 10 value 182376.092204
## final value 182375.920496
## converged
## # weights: 355
## initial value 185989.930562
## iter 10 value 182490.284883
## iter 20 value 182379.918486
## iter 30 value 182378.886914
## final value 182378.835019
## converged
## # weights: 414
## initial value 187584.259758
## final value 182375.451100
## converged
## # weights: 414
## initial value 188647.111140
## iter 10 value 182412.624342
## iter 20 value 182376.190802
## iter 30 value 182375.910859
## final value 182375.896048
## converged
## # weights: 414
## initial value 188594.753985
## iter 10 value 182379.654554
## iter 20 value 182378.629940
## iter 20 value 182378.628791
## iter 20 value 182378.628691
## final value 182378.628691
## converged
## # weights: 473
## initial value 187065.304047
## final value 182375.451100
## converged
## # weights: 473
## initial value 183681.975962
## iter 10 value 182376.110224
## iter 20 value 182375.869992
## final value 182375.861577
## converged
## # weights: 473
## initial value 184976.452850
## iter 10 value 182381.367838
## iter 20 value 182378.501273
## final value 182378.453317
## converged
## # weights: 532
## initial value 189273.422489
## final value 182375.451100
## converged
## # weights: 532
## initial value 188549.679400
## iter 10 value 182400.258876
## iter 20 value 182375.971396
## final value 182375.844316
## converged
## # weights: 532
## initial value 185356.947519
## iter 10 value 182379.663846
## iter 20 value 182378.310036
## final value 182378.300880
## converged
## # weights: 591
## initial value 190255.776089
## final value 182375.451100
## converged
## # weights: 591
## initial value 187597.710422
## iter 10 value 182376.735470
## iter 20 value 182375.832554
## final value 182375.824846
## converged
## # weights: 591
## initial value 185755.642453
## iter 10 value 182380.658495
## iter 20 value 182378.178405
## final value 182378.166245
## converged
## # weights: 60
## initial value 186174.468318
## final value 181468.619800
## converged
## # weights: 60
## initial value 187336.954193
## iter 10 value 181575.164932
## iter 20 value 181470.908516
## iter 30 value 181469.751195
## iter 40 value 181469.523858
## final value 181469.488945
## converged
## # weights: 60
## initial value 187181.088389
## iter 10 value 181495.583633
## iter 20 value 181475.051107
## final value 181474.708722
## converged
## # weights: 119
## initial value 186537.131183
## final value 181468.619800
## converged
## # weights: 119
## initial value 186293.013304
## iter 10 value 181491.805217
## iter 20 value 181469.791772
## iter 30 value 181469.393406
## iter 40 value 181469.313035
## iter 40 value 181469.312586
## iter 40 value 181469.312445
## final value 181469.312445
## converged
## # weights: 119
## initial value 188408.504682
## iter 10 value 181506.802370
## iter 20 value 181474.146060
## final value 181473.598811
## converged
## # weights: 178
## initial value 185329.502426
## final value 181468.619800
## converged
## # weights: 178
## initial value 185378.587102
## iter 10 value 181489.956825
## iter 20 value 181469.408954
## iter 30 value 181469.245320
## final value 181469.220103
## converged
## # weights: 178
## initial value 188068.671663
## iter 10 value 181477.696932
## iter 20 value 181473.111477
## final value 181472.978559
## converged
## # weights: 237
## initial value 185334.712558
## final value 181468.619800
## converged
## # weights: 237
## initial value 186493.871229
## iter 10 value 181503.208097
## iter 20 value 181469.411517
## iter 30 value 181469.208841
## final value 181469.158319
## converged
## # weights: 237
## initial value 186201.215185
## iter 10 value 181544.063005
## iter 20 value 181473.116802
## iter 30 value 181472.560489
## iter 30 value 181472.559597
## iter 30 value 181472.559586
## final value 181472.559586
## converged
## # weights: 296
## initial value 186899.662585
## final value 181468.619800
## converged
## # weights: 296
## initial value 184207.451263
## iter 10 value 181469.362069
## iter 20 value 181469.128771
## final value 181469.118566
## converged
## # weights: 296
## initial value 185450.828425
## iter 10 value 181562.837715
## iter 20 value 181473.617997
## iter 30 value 181472.248561
## iter 30 value 181472.247452
## iter 30 value 181472.247444
## final value 181472.247444
## converged
## # weights: 355
## initial value 186363.762306
## final value 181468.619800
## converged
## # weights: 355
## initial value 184544.019256
## iter 10 value 181469.248277
## final value 181469.086863
## converged
## # weights: 355
## initial value 185274.227983
## iter 10 value 181703.884268
## iter 20 value 181473.302702
## iter 30 value 181472.032124
## final value 181472.000256
## converged
## # weights: 414
## initial value 187346.119233
## final value 181468.619800
## converged
## # weights: 414
## initial value 183348.833697
## iter 10 value 181475.003900
## iter 20 value 181469.114054
## final value 181469.065262
## converged
## # weights: 414
## initial value 185991.500502
## iter 10 value 181475.561571
## iter 20 value 181471.840357
## final value 181471.793785
## converged
## # weights: 473
## initial value 186623.987422
## final value 181468.619800
## converged
## # weights: 473
## initial value 185938.337341
## iter 10 value 181469.444228
## final value 181469.032398
## converged
## # weights: 473
## initial value 188789.878083
## iter 10 value 181512.637684
## iter 20 value 181472.205599
## iter 30 value 181471.642465
## final value 181471.618913
## converged
## # weights: 532
## initial value 185679.348067
## final value 181468.619800
## converged
## # weights: 532
## initial value 185023.951822
## iter 10 value 181469.177902
## iter 20 value 181469.015665
## iter 20 value 181469.014477
## iter 20 value 181469.013752
## final value 181469.013752
## converged
## # weights: 532
## initial value 186911.937916
## iter 10 value 181477.257433
## iter 20 value 181471.583315
## final value 181471.466573
## converged
## # weights: 591
## initial value 185772.759833
## final value 181468.619800
## converged
## # weights: 591
## initial value 184699.281083
## iter 10 value 181478.120299
## iter 20 value 181469.000544
## final value 181468.991842
## converged
## # weights: 591
## initial value 187480.565193
## iter 10 value 181476.508662
## iter 20 value 181471.334663
## iter 20 value 181471.332987
## iter 20 value 181471.332970
## final value 181471.332970
## converged
## # weights: 60
## initial value 186890.757030
## final value 182688.911400
## converged
## # weights: 60
## initial value 186279.881902
## iter 10 value 182796.431693
## iter 20 value 182691.075683
## iter 30 value 182690.038098
## iter 40 value 182689.812200
## final value 182689.780883
## converged
## # weights: 60
## initial value 188770.666418
## iter 10 value 182710.476873
## iter 20 value 182695.617665
## final value 182695.008551
## converged
## # weights: 119
## initial value 185294.501765
## final value 182688.911400
## converged
## # weights: 119
## initial value 186672.629828
## iter 10 value 182829.929523
## iter 20 value 182692.311299
## iter 30 value 182690.078517
## iter 40 value 182689.665733
## final value 182689.608388
## converged
## # weights: 119
## initial value 187894.827757
## iter 10 value 182731.311278
## iter 20 value 182694.097648
## final value 182693.896975
## converged
## # weights: 178
## initial value 189217.028042
## final value 182688.911400
## converged
## # weights: 178
## initial value 188337.826802
## iter 10 value 182717.139621
## iter 20 value 182690.193352
## iter 30 value 182689.660499
## iter 40 value 182689.531379
## final value 182689.523732
## converged
## # weights: 178
## initial value 188192.759100
## iter 10 value 182747.158338
## iter 20 value 182693.615915
## iter 30 value 182693.276042
## iter 30 value 182693.274870
## iter 30 value 182693.274628
## final value 182693.274628
## converged
## # weights: 237
## initial value 187657.256432
## final value 182688.911400
## converged
## # weights: 237
## initial value 184849.369779
## iter 10 value 182689.621271
## iter 20 value 182689.460874
## final value 182689.456147
## converged
## # weights: 237
## initial value 186212.843625
## iter 10 value 182767.141729
## iter 20 value 182693.201811
## final value 182692.856276
## converged
## # weights: 296
## initial value 185055.575756
## final value 182688.911400
## converged
## # weights: 296
## initial value 188077.893674
## iter 10 value 182725.780855
## iter 20 value 182689.997274
## iter 30 value 182689.465705
## final value 182689.410476
## converged
## # weights: 296
## initial value 187406.676051
## iter 10 value 182779.430743
## iter 20 value 182693.172480
## final value 182692.559170
## converged
## # weights: 355
## initial value 188435.911915
## final value 182688.911400
## converged
## # weights: 355
## initial value 186584.544724
## iter 10 value 182689.903621
## iter 20 value 182689.383661
## final value 182689.379876
## converged
## # weights: 355
## initial value 187182.323523
## iter 10 value 182801.330074
## iter 20 value 182692.760481
## final value 182692.294552
## converged
## # weights: 414
## initial value 188810.996985
## final value 182688.911400
## converged
## # weights: 414
## initial value 186393.483868
## iter 10 value 182689.518447
## iter 20 value 182689.352332
## final value 182689.348131
## converged
## # weights: 414
## initial value 184208.999766
## iter 10 value 182696.864440
## iter 20 value 182692.173902
## final value 182692.089150
## converged
## # weights: 473
## initial value 185651.822617
## final value 182688.911400
## converged
## # weights: 473
## initial value 189260.837042
## iter 10 value 182707.216907
## iter 20 value 182690.620909
## iter 30 value 182689.395839
## final value 182689.326388
## converged
## # weights: 473
## initial value 185306.096691
## iter 10 value 182694.391742
## iter 20 value 182691.915598
## iter 20 value 182691.914572
## iter 20 value 182691.914572
## final value 182691.914572
## converged
## # weights: 532
## initial value 187218.926366
## final value 182688.911400
## converged
## # weights: 532
## initial value 189484.437570
## iter 10 value 182723.403291
## iter 20 value 182689.618836
## iter 30 value 182689.306549
## iter 30 value 182689.304968
## iter 30 value 182689.304496
## final value 182689.304496
## converged
## # weights: 532
## initial value 189822.046820
## iter 10 value 182739.890226
## iter 20 value 182692.366780
## iter 30 value 182691.822325
## iter 40 value 182691.787631
## final value 182691.761958
## converged
## # weights: 591
## initial value 189739.461369
## final value 182688.911400
## converged
## # weights: 591
## initial value 184973.916832
## iter 10 value 182698.668592
## iter 20 value 182689.311231
## final value 182689.282795
## converged
## # weights: 591
## initial value 186771.381811
## iter 10 value 182694.872974
## iter 20 value 182691.636800
## final value 182691.627437
## converged
## # weights: 60
## initial value 187559.068123
## final value 182864.875500
## converged
## # weights: 60
## initial value 186744.675581
## iter 10 value 182983.761411
## iter 20 value 182867.526045
## iter 30 value 182866.090462
## iter 40 value 182865.748289
## final value 182865.743955
## converged
## # weights: 60
## initial value 187922.422381
## iter 10 value 182872.176865
## iter 20 value 182870.975370
## final value 182870.972384
## converged
## # weights: 119
## initial value 188676.849060
## final value 182864.875500
## converged
## # weights: 119
## initial value 189069.323660
## iter 10 value 182886.529548
## iter 20 value 182865.693565
## iter 30 value 182865.574977
## final value 182865.569729
## converged
## # weights: 119
## initial value 188743.879373
## iter 10 value 182906.681848
## iter 20 value 182870.054113
## final value 182869.860510
## converged
## # weights: 178
## initial value 189382.248160
## final value 182864.875500
## converged
## # weights: 178
## initial value 188572.507166
## iter 10 value 183029.353380
## iter 20 value 182869.421948
## iter 30 value 182866.012680
## iter 40 value 182865.587271
## final value 182865.478310
## converged
## # weights: 178
## initial value 188784.701199
## iter 10 value 182920.588619
## iter 20 value 182869.962315
## iter 30 value 182869.242722
## final value 182869.239405
## converged
## # weights: 237
## initial value 185190.308067
## final value 182864.875500
## converged
## # weights: 237
## initial value 186886.366925
## iter 10 value 182876.529299
## iter 20 value 182865.629295
## iter 30 value 182865.423914
## final value 182865.419293
## converged
## # weights: 237
## initial value 187327.438911
## iter 10 value 182938.119260
## iter 20 value 182869.353004
## final value 182868.820807
## converged
## # weights: 296
## initial value 188275.077140
## final value 182864.875500
## converged
## # weights: 296
## initial value 188101.116525
## iter 10 value 182913.596891
## iter 20 value 182865.600930
## iter 30 value 182865.399237
## final value 182865.373965
## converged
## # weights: 296
## initial value 187951.648727
## iter 10 value 182962.906438
## iter 20 value 182868.813850
## iter 30 value 182868.507900
## iter 30 value 182868.507362
## iter 30 value 182868.507362
## final value 182868.507362
## converged
## # weights: 355
## initial value 189062.950960
## final value 182864.875500
## converged
## # weights: 355
## initial value 188435.784600
## iter 10 value 182890.364391
## iter 20 value 182865.615678
## final value 182865.345494
## converged
## # weights: 355
## initial value 189157.229939
## iter 10 value 182874.507417
## iter 20 value 182868.319310
## final value 182868.262442
## converged
## # weights: 414
## initial value 187178.483706
## final value 182864.875500
## converged
## # weights: 414
## initial value 186764.306160
## iter 10 value 182865.813345
## iter 20 value 182865.339894
## final value 182865.311178
## converged
## # weights: 414
## initial value 187580.765197
## iter 10 value 183078.911122
## iter 20 value 182873.977098
## iter 30 value 182868.079556
## final value 182868.053360
## converged
## # weights: 473
## initial value 185988.358496
## final value 182864.875500
## converged
## # weights: 473
## initial value 185520.992188
## iter 10 value 182872.206183
## iter 20 value 182865.330153
## iter 30 value 182865.287915
## iter 30 value 182865.287174
## iter 30 value 182865.286814
## final value 182865.286814
## converged
## # weights: 473
## initial value 185815.654038
## iter 10 value 182890.744252
## iter 20 value 182868.021891
## final value 182867.878044
## converged
## # weights: 532
## initial value 185976.086818
## final value 182864.875500
## converged
## # weights: 532
## initial value 189082.147377
## iter 10 value 182918.607443
## iter 20 value 182865.794736
## iter 30 value 182865.379401
## iter 40 value 182865.302929
## final value 182865.276620
## converged
## # weights: 532
## initial value 189593.047513
## iter 10 value 182872.876724
## iter 20 value 182867.758809
## final value 182867.726771
## converged
## # weights: 591
## initial value 186614.411914
## final value 182864.875500
## converged
## # weights: 591
## initial value 186206.014719
## iter 10 value 182868.346987
## iter 20 value 182865.294279
## final value 182865.249856
## converged
## # weights: 591
## initial value 189104.971950
## iter 10 value 182870.678786
## iter 20 value 182867.596385
## final value 182867.590946
## converged
## # weights: 60
## initial value 188987.739441
## final value 183865.761300
## converged
## # weights: 60
## initial value 188388.813578
## iter 10 value 183990.030174
## iter 20 value 183868.229885
## iter 30 value 183867.005383
## iter 40 value 183866.666169
## final value 183866.634512
## converged
## # weights: 60
## initial value 188144.751746
## iter 10 value 183886.509813
## iter 20 value 183871.990227
## final value 183871.865511
## converged
## # weights: 119
## initial value 189787.761003
## final value 183865.761300
## converged
## # weights: 119
## initial value 186789.724794
## iter 10 value 183973.358882
## iter 20 value 183869.179135
## iter 30 value 183866.789351
## iter 40 value 183866.465549
## final value 183866.457063
## converged
## # weights: 119
## initial value 190126.890947
## iter 10 value 183906.583487
## iter 20 value 183870.908155
## final value 183870.751780
## converged
## # weights: 178
## initial value 189805.207382
## final value 183865.761300
## converged
## # weights: 178
## initial value 188917.673600
## iter 10 value 183918.076315
## iter 20 value 183866.521469
## iter 30 value 183866.381800
## final value 183866.364913
## converged
## # weights: 178
## initial value 190809.353768
## iter 10 value 183877.334221
## iter 20 value 183870.507174
## final value 183870.129794
## converged
## # weights: 237
## initial value 189271.267920
## final value 183865.761300
## converged
## # weights: 237
## initial value 186626.970391
## iter 10 value 183976.609884
## iter 20 value 183870.386210
## iter 30 value 183866.657303
## iter 40 value 183866.330359
## final value 183866.309521
## converged
## # weights: 237
## initial value 188821.067334
## iter 10 value 183939.454488
## iter 20 value 183870.161714
## final value 183869.709791
## converged
## # weights: 296
## initial value 190435.447360
## final value 183865.761300
## converged
## # weights: 296
## initial value 190166.713768
## iter 10 value 183936.194976
## iter 20 value 183866.906760
## iter 30 value 183866.304367
## iter 40 value 183866.260370
## iter 40 value 183866.258887
## iter 40 value 183866.258419
## final value 183866.258419
## converged
## # weights: 296
## initial value 190771.173673
## iter 10 value 183874.655463
## iter 20 value 183869.674418
## final value 183869.397692
## converged
## # weights: 355
## initial value 188507.383428
## final value 183865.761300
## converged
## # weights: 355
## initial value 188829.858948
## iter 10 value 183880.717465
## iter 20 value 183866.250726
## final value 183866.227935
## converged
## # weights: 355
## initial value 188196.232532
## iter 10 value 184141.108698
## iter 20 value 183872.204593
## iter 30 value 183869.160035
## final value 183869.148923
## converged
## # weights: 414
## initial value 188946.700881
## final value 183865.761300
## converged
## # weights: 414
## initial value 189759.508581
## iter 10 value 183895.934129
## iter 20 value 183869.528869
## iter 30 value 183866.433037
## iter 40 value 183866.215721
## final value 183866.198241
## converged
## # weights: 414
## initial value 191443.057364
## iter 10 value 183911.372478
## iter 20 value 183869.458004
## final value 183868.942511
## converged
## # weights: 473
## initial value 185446.802874
## final value 183865.761300
## converged
## # weights: 473
## initial value 190633.955519
## iter 10 value 183890.782789
## iter 20 value 183866.323506
## iter 30 value 183866.177135
## final value 183866.173172
## converged
## # weights: 473
## initial value 189982.417050
## iter 10 value 183869.893500
## iter 20 value 183868.770201
## final value 183868.766667
## converged
## # weights: 532
## initial value 190372.601232
## final value 183865.761300
## converged
## # weights: 532
## initial value 187593.004737
## iter 10 value 183866.563618
## iter 20 value 183866.181755
## final value 183866.152024
## converged
## # weights: 532
## initial value 188741.666138
## iter 10 value 183887.574384
## iter 20 value 183868.812792
## final value 183868.615168
## converged
## # weights: 591
## initial value 187965.828044
## final value 183865.761300
## converged
## # weights: 591
## initial value 190041.343470
## iter 10 value 183935.017257
## iter 20 value 183868.071537
## iter 30 value 183866.142201
## final value 183866.135346
## converged
## # weights: 591
## initial value 188441.415246
## iter 10 value 183871.598508
## iter 20 value 183868.524516
## final value 183868.479561
## converged
## # weights: 60
## initial value 186437.648585
## final value 181251.240300
## converged
## # weights: 60
## initial value 184365.664618
## iter 10 value 181337.888139
## iter 20 value 181253.290226
## iter 30 value 181252.343994
## iter 40 value 181252.172995
## final value 181252.108193
## converged
## # weights: 60
## initial value 185837.831858
## iter 10 value 181261.883532
## iter 20 value 181257.450186
## final value 181257.328881
## converged
## # weights: 119
## initial value 184689.334379
## final value 181251.240300
## converged
## # weights: 119
## initial value 186198.131349
## iter 10 value 181274.999879
## iter 20 value 181252.347565
## iter 30 value 181252.054654
## iter 40 value 181251.943338
## final value 181251.934174
## converged
## # weights: 119
## initial value 187155.443355
## iter 10 value 181295.378796
## iter 20 value 181257.092797
## iter 30 value 181256.221694
## final value 181256.218690
## converged
## # weights: 178
## initial value 187642.516268
## final value 181251.240300
## converged
## # weights: 178
## initial value 183901.694969
## iter 10 value 181272.190857
## iter 20 value 181252.341216
## iter 30 value 181251.880909
## final value 181251.853909
## converged
## # weights: 178
## initial value 186300.737074
## iter 10 value 181313.480624
## iter 20 value 181256.384184
## final value 181255.598883
## converged
## # weights: 237
## initial value 186185.387544
## final value 181251.240300
## converged
## # weights: 237
## initial value 184619.814101
## iter 10 value 181261.485684
## iter 20 value 181251.955273
## iter 30 value 181251.807346
## final value 181251.779762
## converged
## # weights: 237
## initial value 185332.904897
## iter 10 value 181326.037992
## iter 20 value 181255.665819
## iter 30 value 181255.180584
## iter 30 value 181255.179681
## iter 30 value 181255.179675
## final value 181255.179675
## converged
## # weights: 296
## initial value 185465.861691
## final value 181251.240300
## converged
## # weights: 296
## initial value 184007.410624
## iter 10 value 181252.407097
## iter 20 value 181251.759326
## final value 181251.737882
## converged
## # weights: 296
## initial value 184070.084683
## iter 10 value 181258.781337
## iter 20 value 181254.893989
## final value 181254.867632
## converged
## # weights: 355
## initial value 186763.565454
## final value 181251.240300
## converged
## # weights: 355
## initial value 185542.737826
## iter 10 value 181253.068503
## iter 20 value 181251.739048
## final value 181251.702068
## converged
## # weights: 355
## initial value 186147.504834
## iter 10 value 181358.938406
## iter 20 value 181255.296225
## final value 181254.619892
## converged
## # weights: 414
## initial value 188187.832009
## final value 181251.240300
## converged
## # weights: 414
## initial value 184299.689296
## iter 10 value 181252.029430
## final value 181251.678987
## converged
## # weights: 414
## initial value 187396.129003
## iter 10 value 181262.300324
## iter 20 value 181254.512819
## final value 181254.421215
## converged
## # weights: 473
## initial value 187713.842738
## final value 181251.240300
## converged
## # weights: 473
## initial value 183415.517024
## iter 10 value 181258.781387
## iter 20 value 181251.664584
## final value 181251.651973
## converged
## # weights: 473
## initial value 183466.072685
## iter 10 value 181276.672170
## iter 20 value 181254.334326
## final value 181254.242647
## converged
## # weights: 532
## initial value 187456.011907
## final value 181251.240300
## converged
## # weights: 532
## initial value 187341.225575
## iter 10 value 181279.427852
## iter 20 value 181251.864308
## iter 30 value 181251.689323
## final value 181251.649501
## converged
## # weights: 532
## initial value 183930.038829
## iter 10 value 181326.816020
## iter 20 value 181256.132565
## iter 30 value 181254.140382
## iter 40 value 181254.089658
## final value 181254.086843
## converged
## # weights: 591
## initial value 187152.256022
## final value 181251.240300
## converged
## # weights: 591
## initial value 184878.178749
## iter 10 value 181252.068125
## iter 20 value 181251.615824
## iter 20 value 181251.615020
## iter 20 value 181251.614572
## final value 181251.614572
## converged
## # weights: 591
## initial value 185039.162625
## iter 10 value 181259.108127
## iter 20 value 181253.973148
## final value 181253.952553
## converged
## # weights: 60
## initial value 189253.948103
## final value 184178.041300
## converged
## # weights: 60
## initial value 189031.769559
## iter 10 value 184306.426858
## iter 20 value 184180.560110
## iter 30 value 184179.187366
## final value 184178.911860
## converged
## # weights: 60
## initial value 190080.103883
## iter 10 value 184188.645891
## iter 20 value 184184.173221
## final value 184184.146150
## converged
## # weights: 119
## initial value 188108.736077
## final value 184178.041300
## converged
## # weights: 119
## initial value 189103.646700
## iter 10 value 184317.475218
## iter 20 value 184181.318078
## iter 30 value 184179.097684
## iter 40 value 184178.800498
## final value 184178.740660
## converged
## # weights: 119
## initial value 189210.387708
## iter 10 value 184217.359461
## iter 20 value 184183.258588
## final value 184183.039850
## converged
## # weights: 178
## initial value 187289.729723
## final value 184178.041300
## converged
## # weights: 178
## initial value 189771.858005
## iter 10 value 184218.440933
## iter 20 value 184179.220796
## iter 30 value 184178.765149
## iter 40 value 184178.647469
## final value 184178.643571
## converged
## # weights: 178
## initial value 189662.165325
## iter 10 value 184233.056651
## iter 20 value 184183.207487
## iter 30 value 184182.413367
## final value 184182.410415
## converged
## # weights: 237
## initial value 188456.003964
## final value 184178.041300
## converged
## # weights: 237
## initial value 188525.394201
## iter 10 value 184189.034557
## iter 20 value 184178.769287
## iter 30 value 184178.597736
## final value 184178.584009
## converged
## # weights: 237
## initial value 190215.030342
## iter 10 value 184250.880285
## iter 20 value 184182.523401
## iter 30 value 184181.993238
## iter 30 value 184181.991792
## iter 30 value 184181.991792
## final value 184181.991792
## converged
## # weights: 296
## initial value 187840.645318
## final value 184178.041300
## converged
## # weights: 296
## initial value 187439.169038
## iter 10 value 184179.406692
## iter 20 value 184178.601595
## iter 30 value 184178.544081
## final value 184178.539957
## converged
## # weights: 296
## initial value 188467.421707
## iter 10 value 184265.764705
## iter 20 value 184182.060144
## iter 30 value 184181.679048
## iter 30 value 184181.677855
## iter 30 value 184181.677702
## final value 184181.677702
## converged
## # weights: 355
## initial value 190659.247590
## final value 184178.041300
## converged
## # weights: 355
## initial value 189315.203373
## iter 10 value 184179.659925
## iter 20 value 184178.615061
## iter 30 value 184178.515088
## final value 184178.507459
## converged
## # weights: 355
## initial value 187766.608181
## iter 10 value 184185.379888
## iter 20 value 184181.492549
## final value 184181.428792
## converged
## # weights: 414
## initial value 191256.972851
## final value 184178.041300
## converged
## # weights: 414
## initial value 187387.806436
## iter 10 value 184180.276785
## iter 20 value 184178.589460
## iter 30 value 184178.492275
## final value 184178.477863
## converged
## # weights: 414
## initial value 189862.510604
## iter 10 value 184184.822953
## final value 184181.415255
## converged
## # weights: 473
## initial value 188535.419223
## final value 184178.041300
## converged
## # weights: 473
## initial value 188906.596932
## iter 10 value 184178.605672
## final value 184178.456067
## converged
## # weights: 473
## initial value 188384.431166
## iter 10 value 184181.587333
## final value 184181.047158
## converged
## # weights: 532
## initial value 188824.832460
## final value 184178.041300
## converged
## # weights: 532
## initial value 191126.754436
## iter 10 value 184200.749583
## iter 20 value 184178.634926
## iter 30 value 184178.452124
## final value 184178.431998
## converged
## # weights: 532
## initial value 191646.482658
## iter 10 value 184231.191376
## iter 20 value 184180.982363
## final value 184180.896953
## converged
## # weights: 591
## initial value 190525.718848
## final value 184178.041300
## converged
## # weights: 591
## initial value 189195.498785
## iter 10 value 184178.815899
## iter 20 value 184178.424766
## final value 184178.415054
## converged
## # weights: 591
## initial value 187667.812667
## iter 10 value 184183.850464
## iter 20 value 184180.766635
## final value 184180.761355
## converged
## # weights: 60
## initial value 187432.392617
## final value 182614.133800
## converged
## # weights: 60
## initial value 185265.597565
## iter 10 value 182687.821176
## iter 20 value 182616.226507
## iter 30 value 182615.245392
## iter 40 value 182615.014796
## final value 182615.001944
## converged
## # weights: 60
## initial value 186046.997547
## iter 10 value 182622.062513
## iter 20 value 182620.233797
## final value 182620.230349
## converged
## # weights: 119
## initial value 186506.712056
## final value 182614.133800
## converged
## # weights: 119
## initial value 185996.847596
## iter 10 value 182728.010068
## iter 20 value 182617.247958
## iter 30 value 182615.190247
## iter 40 value 182614.872471
## iter 40 value 182614.870674
## iter 40 value 182614.869917
## final value 182614.869917
## converged
## # weights: 119
## initial value 186913.139266
## iter 10 value 182652.177225
## iter 20 value 182619.310022
## final value 182619.119353
## converged
## # weights: 178
## initial value 188918.094136
## final value 182614.133800
## converged
## # weights: 178
## initial value 186715.601301
## iter 10 value 182641.271796
## iter 20 value 182615.703249
## iter 30 value 182614.838681
## iter 40 value 182614.741109
## final value 182614.735217
## converged
## # weights: 178
## initial value 187042.359203
## iter 10 value 182677.599839
## iter 20 value 182618.855834
## final value 182618.497497
## converged
## # weights: 237
## initial value 187852.075738
## final value 182614.133800
## converged
## # weights: 237
## initial value 187046.291871
## iter 10 value 182625.425804
## iter 20 value 182614.861530
## iter 30 value 182614.683195
## final value 182614.673592
## converged
## # weights: 237
## initial value 188278.992605
## iter 10 value 182687.864668
## iter 20 value 182619.131490
## iter 30 value 182618.162756
## final value 182618.078442
## converged
## # weights: 296
## initial value 187847.076096
## final value 182614.133800
## converged
## # weights: 296
## initial value 185133.272842
## iter 10 value 182614.941082
## iter 20 value 182614.641841
## final value 182614.637057
## converged
## # weights: 296
## initial value 188892.776614
## iter 10 value 182625.334375
## iter 20 value 182618.043596
## final value 182617.765095
## converged
## # weights: 355
## initial value 187042.957595
## final value 182614.133800
## converged
## # weights: 355
## initial value 187500.883009
## iter 10 value 182615.556595
## iter 20 value 182614.718780
## iter 30 value 182614.606810
## final value 182614.596748
## converged
## # weights: 355
## initial value 189415.945037
## iter 10 value 182632.973428
## iter 20 value 182617.673252
## iter 30 value 182617.528446
## final value 182617.517252
## converged
## # weights: 414
## initial value 186626.450623
## final value 182614.133800
## converged
## # weights: 414
## initial value 189543.493424
## iter 10 value 182642.202449
## iter 20 value 182614.711789
## final value 182614.575519
## converged
## # weights: 414
## initial value 187522.345480
## iter 10 value 182735.607290
## iter 20 value 182618.613928
## iter 30 value 182617.312924
## iter 30 value 182617.311540
## iter 30 value 182617.311342
## final value 182617.311342
## converged
## # weights: 473
## initial value 186220.758121
## final value 182614.133800
## converged
## # weights: 473
## initial value 187315.553740
## iter 10 value 182614.721270
## iter 20 value 182614.553220
## final value 182614.548930
## converged
## # weights: 473
## initial value 184906.147745
## iter 10 value 182657.587292
## iter 20 value 182618.283498
## iter 30 value 182617.140873
## final value 182617.136776
## converged
## # weights: 532
## initial value 188657.027754
## final value 182614.133800
## converged
## # weights: 532
## initial value 185484.592109
## iter 10 value 182620.349269
## iter 20 value 182614.586275
## final value 182614.526058
## converged
## # weights: 532
## initial value 187266.878304
## iter 10 value 182619.969171
## iter 20 value 182617.015300
## final value 182616.983629
## converged
## # weights: 591
## initial value 186830.703879
## final value 182614.133800
## converged
## # weights: 591
## initial value 186015.561978
## iter 10 value 182623.307713
## iter 20 value 182614.507022
## iter 20 value 182614.505847
## iter 20 value 182614.505570
## final value 182614.505570
## converged
## # weights: 591
## initial value 188198.182276
## iter 10 value 182619.786175
## iter 20 value 182616.869081
## final value 182616.849224
## converged
## Warning in nominalTrainWorkflow(x = x, y = y, wts = weights, info =
## trainInfo, : There were missing values in resampled performance measures.
## # weights: 60
## initial value 208658.431312
## final value 202668.392600
## converged
## RMSE Rsquared MAE
## 39.32750 NA 39.29659
3] Support Vector Machine -
perfsvm = model.eval('svmRadial')
## RMSE Rsquared MAE
## 1.2104413 0.4357604 0.9917534
4] Multivariate Adaptive Regression Splines -
marsGrid = expand.grid(degree = 1:2, nprune = 2:38)
perfmars = model.eval('earth', marsGrid)
## RMSE Rsquared MAE
## 1.1162025 0.5346722 0.8678310
df.perf = rbind(data.frame(Name = 'KNN', RMSE = perfknn[1]), data.frame(Name= 'NN', RMSE = perfnn[1]) , data.frame(Name = 'SVM', RMSE = perfsvm[1]), data.frame(Name = 'MARS', RMSE = perfmars[1]))
ggplot(data = df.perf, aes(x = Name, y = RMSE, fill=Name)) +
geom_bar(stat="identity", position=position_dodge()) +
geom_text(aes(label=RMSE), vjust=1, color="white",
position = position_dodge(0.9), size=3.5)
b. Which predictors are most important in the optimal nonlinear regression model? Do either the biological or process variables dominate the list? How do the top ten important predictors compare to the top ten predictors from the optimal linear model?
marsGrid = expand.grid(degree = 1:2, nprune = 2:38)
MARSModel = train(x = df.train.x, y = df.train.y, method = 'earth', tuneGrid = marsGrid, preProcess = c('center', 'scale'), trControl = trainControl(method='cv'))
print(varImp(MARSModel))
## earth variable importance
##
## only 20 most important variables shown (out of 57)
##
## Overall
## ManufacturingProcess32 100.000
## ManufacturingProcess09 70.413
## ManufacturingProcess13 70.251
## BiologicalMaterial02 57.591
## BiologicalMaterial06 50.058
## ManufacturingProcess17 39.753
## ManufacturingProcess42 31.938
## ManufacturingProcess43 29.620
## ManufacturingProcess28 28.164
## ManufacturingProcess06 22.935
## BiologicalMaterial07 16.488
## ManufacturingProcess05 16.488
## BiologicalMaterial10 7.311
## ManufacturingProcess39 0.000
## ManufacturingProcess04 0.000
## ManufacturingProcess20 0.000
## ManufacturingProcess33 0.000
## ManufacturingProcess26 0.000
## ManufacturingProcess08 0.000
## ManufacturingProcess24 0.000
From the above list of top 20 important variables we can see that manufacturing process variables dominate the important variable list.
summary(MARSModel)
## Call: earth(x=data.frame[132,57], y=c(37.86,40.19,4...), keepxy=TRUE,
## degree=2, nprune=15)
##
## coefficients
## (Intercept) 38.759002
## h(-1.01489-BiologicalMaterial10) -1.735577
## h(-0.225114-ManufacturingProcess17) 1.209577
## h(-1.26221-ManufacturingProcess32) 4.272698
## h(ManufacturingProcess32- -1.26221) 0.773730
## BiologicalMaterial07 * h(ManufacturingProcess05- -0.901682) -0.496288
## h(0.406326-BiologicalMaterial02) * h(ManufacturingProcess09- -0.96278) 2.272730
## h(BiologicalMaterial02-0.406326) * h(ManufacturingProcess09- -0.96278) 0.628935
## h(-0.327034-BiologicalMaterial06) * h(ManufacturingProcess05- -0.901682) -0.853252
## h(-0.020428-BiologicalMaterial06) * h(ManufacturingProcess09- -0.96278) -2.986868
## h(0.0730604-ManufacturingProcess06) * h(ManufacturingProcess09- -0.96278) -0.799392
## h(-0.317952-ManufacturingProcess09) * h(ManufacturingProcess13- -1.34838) -0.229493
## h(ManufacturingProcess09- -0.96278) * h(0.144637-ManufacturingProcess42) -0.219491
## h(ManufacturingProcess13- -1.34838) * h(-0.6113-ManufacturingProcess43) -1.159074
## h(0.775286-ManufacturingProcess28) * h(ManufacturingProcess32- -1.26221) 0.277827
##
## Selected 15 of 36 terms, and 13 of 57 predictors
## Termination condition: RSq changed by less than 0.001 at 36 terms
## Importance: ManufacturingProcess32, ManufacturingProcess09, ...
## Number of terms at each degree of interaction: 1 4 10
## GCV 0.834982 RSS 58.29693 GRSq 0.777723 RSq 0.8806302
From the MARS model summary we can see that top 10 important predictor are different than top ten predictor of the optimum linear model
c. Explore the relationships between the top predictors and the response for the predictors that are unique to the optimal nonlinear regression model. Do these plots reveal intuition about the biological or process predictors and their relationship with yield?
Plot correltion matrix of data
## Warning: package 'corrplot' was built under R version 3.6.1
## corrplot 0.84 loaded
## Warning: package 'PerformanceAnalytics' was built under R version 3.6.3
## Loading required package: xts
## Warning: package 'xts' was built under R version 3.6.2
## Loading required package: zoo
## Warning: package 'zoo' was built under R version 3.6.2
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
##
## Attaching package: 'PerformanceAnalytics'
## The following object is masked from 'package:graphics':
##
## legend
From the above correlation graph between top 10 important predictors and outcome variable (Yield) We can see that there exist a non linear relationship between important predictors and outcome variable. No wonder second degree MARS model is proving to be optimal model for this dataset