Load .Rdata
load(file = "D:/Penelitian/Output/env_6 Cluster.RData")
2 Cluster Confusion Matrix
Signifikansi Parameter 2 Cluster
library(flexmix)
## Loading required package: lattice
summary(sign_par)
## $Comp.1
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 7.905055 4.162193 1.8993 0.057531 .
## X1 -7.875130 3.295167 -2.3899 0.016853 *
## X2 4.273495 1.619794 2.6383 0.008332 **
## X3 3.187577 1.676637 1.9012 0.057279 .
## X5 -0.094602 0.042595 -2.2209 0.026355 *
## X6 0.582451 1.221574 0.4768 0.633502
## X7 -0.198651 0.067048 -2.9628 0.003048 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## $Comp.2
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -241.21387 121.71668 -1.9818 0.04751 *
## X1 30.76040 28.09193 1.0950 0.27352
## X2 -17.88971 14.77444 -1.2109 0.22595
## X3 -4.22680 9.93696 -0.4254 0.67057
## X5 0.14564 0.18111 0.8041 0.42132
## X6 56.95453 26.50663 2.1487 0.03166 *
## X7 2.97991 1.44129 2.0675 0.03868 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Train
train_cm
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 957 74
## 1 43 1026
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 0.944285714 0.888475330 0.933600812 0.953707947 0.523809524
## AccuracyPValue McnemarPValue
## 0.000000000 0.005545667
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.9570000 0.9327273 0.9282250
## Neg Pred Value Precision Recall
## 0.9597755 0.9282250 0.9570000
## F1 Prevalence Detection Rate
## 0.9423929 0.4761905 0.4557143
## Detection Prevalence Balanced Accuracy
## 0.4909524 0.9448636
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
Test
test_cm
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 558 29
## 1 344 24
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 6.094241e-01 1.881850e-02 5.776590e-01 6.405122e-01 9.445026e-01
## AccuracyPValue McnemarPValue
## 1.000000e+00 1.950640e-59
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.61862528 0.45283019 0.95059625
## Neg Pred Value Precision Recall
## 0.06521739 0.95059625 0.61862528
## F1 Prevalence Detection Rate
## 0.74949631 0.94450262 0.58429319
## Detection Prevalence Balanced Accuracy
## 0.61465969 0.53572773
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
3 Cluster Confusion Matrix
Train
train_cm3
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 350 339
## 1 650 761
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 5.290476e-01 4.241782e-02 5.074327e-01 5.505814e-01 5.238095e-01
## AccuracyPValue McnemarPValue
## 3.233003e-01 6.366009e-23
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.3500000 0.6918182 0.5079826
## Neg Pred Value Precision Recall
## 0.5393338 0.5079826 0.3500000
## F1 Prevalence Detection Rate
## 0.4144464 0.4761905 0.1666667
## Detection Prevalence Balanced Accuracy
## 0.3280952 0.5209091
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
Test
test_cm3
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 624 38
## 1 278 15
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 6.691099e-01 -8.043504e-03 6.382570e-01 6.989158e-01 9.445026e-01
## AccuracyPValue McnemarPValue
## 1.000000e+00 3.302958e-41
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.69179601 0.28301887 0.94259819
## Neg Pred Value Precision Recall
## 0.05119454 0.94259819 0.69179601
## F1 Prevalence Detection Rate
## 0.79795396 0.94450262 0.65340314
## Detection Prevalence Balanced Accuracy
## 0.69319372 0.48740744
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
4 Cluster Confusion Matrix
Train
train_cm4
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 1000 1
## 1 0 1099
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 0.9995238 0.9990455 0.9973497 0.9999879 0.5238095
## AccuracyPValue McnemarPValue
## 0.0000000 1.0000000
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 1.0000000 0.9990909 0.9990010
## Neg Pred Value Precision Recall
## 1.0000000 0.9990010 1.0000000
## F1 Prevalence Detection Rate
## 0.9995002 0.4761905 0.4761905
## Detection Prevalence Balanced Accuracy
## 0.4766667 0.9995455
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
Test
test_cm4
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 56 2
## 1 846 51
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 1.120419e-01 2.866402e-03 9.273414e-02 1.337779e-01 9.445026e-01
## AccuracyPValue McnemarPValue
## 1.000000e+00 2.910744e-184
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.06208426 0.96226415 0.96551724
## Neg Pred Value Precision Recall
## 0.05685619 0.96551724 0.06208426
## F1 Prevalence Detection Rate
## 0.11666667 0.94450262 0.05863874
## Detection Prevalence Balanced Accuracy
## 0.06073298 0.51217420
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
5 Cluster Confusion Matrix
Train
train_cm5
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 510 0
## 1 490 1100
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 7.666667e-01 5.216179e-01 7.479738e-01 7.846122e-01 5.238095e-01
## AccuracyPValue McnemarPValue
## 8.841445e-117 3.877458e-108
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.5100000 1.0000000 1.0000000
## Neg Pred Value Precision Recall
## 0.6918239 1.0000000 0.5100000
## F1 Prevalence Detection Rate
## 0.6754967 0.4761905 0.2428571
## Detection Prevalence Balanced Accuracy
## 0.2428571 0.7550000
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
Test
test_cm5
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 441 23
## 1 461 30
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 4.931937e-01 1.123913e-02 4.610244e-01 5.254051e-01 9.445026e-01
## AccuracyPValue McnemarPValue
## 1.000000e+00 8.400260e-88
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.4889135 0.5660377 0.9504310
## Neg Pred Value Precision Recall
## 0.0610998 0.9504310 0.4889135
## F1 Prevalence Detection Rate
## 0.6456808 0.9445026 0.4617801
## Detection Prevalence Balanced Accuracy
## 0.4858639 0.5274756
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
6 Cluster Confusion Matrix
Train
train_cm6
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 1000 0
## 1 0 1100
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 1.0000000 1.0000000 0.9982449 1.0000000 0.5238095
## AccuracyPValue McnemarPValue
## 0.0000000 NaN
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 1.0000000 1.0000000 1.0000000
## Neg Pred Value Precision Recall
## 1.0000000 1.0000000 1.0000000
## F1 Prevalence Detection Rate
## 1.0000000 0.4761905 0.4761905
## Detection Prevalence Balanced Accuracy
## 0.4761905 1.0000000
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"
Test
test_cm6
## $positive
## [1] "0"
##
## $table
## Reference
## Prediction 0 1
## 0 763 49
## 1 139 4
##
## $overall
## Accuracy Kappa AccuracyLower AccuracyUpper AccuracyNull
## 8.031414e-01 -4.370371e-02 7.764806e-01 8.279175e-01 9.445026e-01
## AccuracyPValue McnemarPValue
## 1.000000e+00 8.527294e-11
##
## $byClass
## Sensitivity Specificity Pos Pred Value
## 0.84589800 0.07547170 0.93965517
## Neg Pred Value Precision Recall
## 0.02797203 0.93965517 0.84589800
## F1 Prevalence Detection Rate
## 0.89031505 0.94450262 0.79895288
## Detection Prevalence Balanced Accuracy
## 0.85026178 0.46068485
##
## $mode
## [1] "sens_spec"
##
## $dots
## list()
##
## attr(,"class")
## [1] "confusionMatrix"