With missing values.
After removing the missing values.
##
## Call:
## FAMD(base = finalData[, -c(1, 2)], ncp = 25, graph = FALSE)
##
##
## Eigenvalues
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5 Dim.6
## Variance 5.553 2.656 2.172 1.868 1.351 1.165
## % of var. 22.211 10.624 8.689 7.471 5.404 4.658
## Cumulative % of var. 22.211 32.835 41.525 48.996 54.400 59.058
## Dim.7 Dim.8 Dim.9 Dim.10 Dim.11 Dim.12
## Variance 1.079 1.001 1.000 0.998 0.927 0.862
## % of var. 4.315 4.004 4.001 3.990 3.708 3.449
## Cumulative % of var. 63.373 67.378 71.379 75.369 79.077 82.526
## Dim.13 Dim.14 Dim.15 Dim.16 Dim.17 Dim.18
## Variance 0.795 0.696 0.625 0.433 0.416 0.396
## % of var. 3.181 2.785 2.499 1.732 1.662 1.583
## Cumulative % of var. 85.707 88.492 90.991 92.723 94.385 95.968
## Dim.19 Dim.20 Dim.21 Dim.22 Dim.23 Dim.24
## Variance 0.311 0.273 0.213 0.143 0.062 0.006
## % of var. 1.243 1.093 0.853 0.572 0.247 0.022
## Cumulative % of var. 97.211 98.304 99.158 99.730 99.976 99.999
## Dim.25
## Variance 0.000
## % of var. 0.001
## Cumulative % of var. 100.000
##
## Individuals (the 10 first)
## Dist Dim.1 ctr cos2
## 1 | 3.811 | -1.463 0.000 0.147 |
## 2 | 3.825 | -1.454 0.000 0.144 |
## 3 | 3.801 | -1.499 0.000 0.155 |
## 4 | 3.835 | -1.600 0.000 0.174 |
## 5 | 3.840 | -2.025 0.001 0.278 |
## 6 | 3.862 | -1.916 0.001 0.246 |
## 7 | 3.822 | -1.963 0.001 0.264 |
## 8 | 3.843 | -1.960 0.001 0.260 |
## 9 | 3.843 | -1.986 0.001 0.267 |
## 10 | 3.868 | -1.923 0.001 0.247 |
## Dim.2 ctr cos2 Dim.3
## 1 -0.307 0.000 0.007 | 0.369
## 2 -0.310 0.000 0.007 | 0.371
## 3 -0.292 0.000 0.006 | 0.435
## 4 -0.300 0.000 0.006 | 0.480
## 5 0.522 0.000 0.019 | -0.094
## 6 0.533 0.000 0.019 | -0.143
## 7 0.468 0.000 0.015 | -0.200
## 8 0.510 0.000 0.018 | -0.148
## 9 0.499 0.000 0.017 | -0.136
## 10 0.509 0.000 0.017 | -0.165
## ctr cos2
## 1 0.000 0.009 |
## 2 0.000 0.009 |
## 3 0.000 0.013 |
## 4 0.000 0.016 |
## 5 0.000 0.001 |
## 6 0.000 0.001 |
## 7 0.000 0.003 |
## 8 0.000 0.001 |
## 9 0.000 0.001 |
## 10 0.000 0.002 |
##
## Continuous variables (the 10 first)
## Dim.1 ctr cos2 Dim.2
## LaboratorioPassante150meshpv | 0.019 0.006 0.000 | -0.006
## MoinhoAlimentacaoTaxaMineriomv | -0.111 0.220 0.012 | -0.047
## MoinhoAlimentacaoTaxaMineriopv | 0.097 0.169 0.009 | 0.386
## MoinhoAlimentacaoVazaoAguapv | 0.086 0.132 0.007 | 0.241
## MoinhoCaixaDescargaCaixaABombaRotacaomv | 0.803 11.599 0.644 | 0.110
## MoinhoCaixaDescargaCaixaANivelpv | 0.916 15.114 0.839 | 0.135
## MoinhoCaixaDescargaCaixaRNivelpv | -0.797 11.437 0.635 | -0.216
## MoinhoCaixaDescargaVazaoAguamv | -0.309 1.722 0.096 | 0.582
## MoinhoCaixaDescargaVazaoAguapv | 0.052 0.048 0.003 | 0.444
## MoinhoHidrociclonesDensidadepv | 0.134 0.321 0.018 | 0.259
## ctr cos2 Dim.3 ctr
## LaboratorioPassante150meshpv 0.001 0.000 | 0.011 0.006
## MoinhoAlimentacaoTaxaMineriomv 0.083 0.002 | -0.248 2.825
## MoinhoAlimentacaoTaxaMineriopv 5.624 0.149 | 0.454 9.479
## MoinhoAlimentacaoVazaoAguapv 2.195 0.058 | -0.091 0.381
## MoinhoCaixaDescargaCaixaABombaRotacaomv 0.458 0.012 | -0.023 0.024
## MoinhoCaixaDescargaCaixaANivelpv 0.686 0.018 | -0.098 0.443
## MoinhoCaixaDescargaCaixaRNivelpv 1.760 0.047 | 0.171 1.350
## MoinhoCaixaDescargaVazaoAguamv 12.765 0.339 | -0.107 0.526
## MoinhoCaixaDescargaVazaoAguapv 7.406 0.197 | 0.435 8.700
## MoinhoHidrociclonesDensidadepv 2.529 0.067 | 0.392 7.062
## cos2
## LaboratorioPassante150meshpv 0.000 |
## MoinhoAlimentacaoTaxaMineriomv 0.061 |
## MoinhoAlimentacaoTaxaMineriopv 0.206 |
## MoinhoAlimentacaoVazaoAguapv 0.008 |
## MoinhoCaixaDescargaCaixaABombaRotacaomv 0.001 |
## MoinhoCaixaDescargaCaixaANivelpv 0.010 |
## MoinhoCaixaDescargaCaixaRNivelpv 0.029 |
## MoinhoCaixaDescargaVazaoAguamv 0.011 |
## MoinhoCaixaDescargaVazaoAguapv 0.189 |
## MoinhoHidrociclonesDensidadepv 0.153 |
##
## Categories (the 10 first)
## Dim.1 ctr cos2
## 0 | 0.700 1.114 0.498
## 1 | -1.639 2.608 0.498
## 0 | 1.557 0.002 0.001
## 1 | 0.000 0.000 0.001
## 0 | -1.409 1.230 0.323
## 1 | 0.333 0.290 0.323
## 0 | -2.073 7.333 0.963
## 1 | 2.303 8.149 0.963
## 0 | 1.260 0.077 0.022
## 1 | -0.019 0.001 0.022
## v.test Dim.2 ctr
## 0 142.587 | -0.536 2.856
## 1 -142.587 | 1.256 6.688
## 0 3.100 | 1.546 0.008
## 1 -3.100 | 0.000 0.000
## 0 -91.123 | -0.217 0.127
## 1 91.123 | 0.051 0.030
## 0 -290.827 | -0.241 0.433
## 1 290.827 | 0.268 0.482
## 0 20.651 | -1.558 0.514
## 1 -20.651 | 0.024 0.008
## cos2 v.test Dim.3
## 0 0.292 -157.921 | 0.227
## 1 0.292 157.921 | -0.530
## 0 0.001 4.450 | -1.776
## 1 0.001 -4.450 | 0.000
## 0 0.008 -20.247 | -0.625
## 1 0.008 20.247 | 0.147
## 0 0.013 -48.905 | 0.159
## 1 0.013 48.905 | -0.177
## 0 0.034 -36.916 | -1.453
## 1 0.034 36.916 | 0.022
## ctr cos2 v.test
## 0 0.762 0.052 73.765 |
## 1 1.784 0.052 -73.765 |
## 0 0.015 0.001 -5.653 |
## 1 0.000 0.001 5.653 |
## 0 1.579 0.064 -64.592 |
## 1 0.373 0.064 64.592 |
## 0 0.283 0.006 35.732 |
## 1 0.314 0.006 -35.732 |
## 0 0.668 0.030 -38.060 |
## 1 0.010 0.030 38.060 |
## Best Dimension
## 1 Dim.9
## 2 Dim.7
## 3 Dim.3
## 4 Dim.5
## 5 Dim.1
## 6 Dim.1
## 7 Dim.1
## 8 Dim.2
## 9 Dim.6
## 10 Dim.4
## 11 Dim.2
## 12 Dim.3
## 13 Dim.13
##
## Call:
## lm(formula = Potencia ~ . - val.Dim9, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -70.675 -4.543 -1.549 1.947 60.173
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.613e+01 2.235e+00 16.161 < 2e-16 ***
## val.Dim1 3.981e-03 1.979e-03 2.012 0.0442 *
## val.Dim2 -3.423e-02 2.951e-03 -11.597 < 2e-16 ***
## val.Dim3 2.579e+00 1.045e-03 2467.055 < 2e-16 ***
## val.Dim4 -1.791e+02 8.294e+00 -21.588 < 2e-16 ***
## val.Dim5 -6.849e-01 1.465e-02 -46.760 < 2e-16 ***
## val.Dim6 -1.376e-01 5.447e-03 -25.261 < 2e-16 ***
## val.Dim7 7.929e-01 1.686e-02 47.030 < 2e-16 ***
## val.Dim13 -1.898e-01 3.565e-02 -5.323 1.02e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.564 on 98374 degrees of freedom
## Multiple R-squared: 0.9899, Adjusted R-squared: 0.9899
## F-statistic: 1.206e+06 on 8 and 98374 DF, p-value: < 2.2e-16
As duas primeiras dimensões são as mais significantes. A primeira dimensão pode ser interpretada como uma combinação linear das variáveis MoinhoCaixaDescargaCaixaABombaRotacaomv, MoinhoCaixaDescargaCaixaANivelpv e MoinhoCaixaDescargaCaixaRNivelpv. Já a segunda dimensão é uma combinação das variáveis MoinhoCaixaDescargaVazaoAguamv e MoinhoHidrociclonesPressaopv.
Dim = coordenate for each dimension.
ctr = contribution for the construction of that dimension.
cos = quality of representation. If it is close to 1 it means that it is well projected on the dimension.
v.test = significant test. If it is smaller than -2 or bigger than 2 it means that the observation’s coordenate is significant smaller or bigger than 0.
##
## Call:
## lm(formula = MoinhoMotorMoinhoPotenciapv ~ . - MoinhoAlimentacaoTaxaMineriopermissaohmi -
## OptProcessPulsoLido - MoinhoHidrociclonesDensidadehmi - MoinhoCaixaDescargaCaixaRBombaLigado -
## LaboratorioPassante150meshpv - PSTPassante150meshMedianapv -
## MoinhoBombaDePocoLigada + Lag, data = finalData[, -c(1, 2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -1135.15 -2.85 0.16 3.08 1051.83
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) -1.573e+03 3.560e+00 -441.77
## MoinhoAlimentacaoTaxaMineriomv -3.886e+00 1.974e-02 -196.86
## MoinhoAlimentacaoTaxaMineriopv 6.667e-01 2.858e-03 233.29
## MoinhoAlimentacaoVazaoAguapv 4.806e-01 7.054e-03 68.13
## MoinhoCaixaDescargaCaixaABombaRotacaomv -2.151e+00 1.232e-02 -174.60
## MoinhoCaixaDescargaCaixaANivelpv 3.298e-01 6.675e-03 49.40
## MoinhoCaixaDescargaCaixaRNivelpv 3.442e-01 3.683e-03 93.47
## MoinhoCaixaDescargaVazaoAguamv -2.322e-01 2.093e-03 -110.95
## MoinhoCaixaDescargaVazaoAguapv 4.983e-01 2.068e-03 240.97
## MoinhoHidrociclonesDensidadepv 1.734e+03 2.336e+00 741.95
## MoinhoHidrociclonesPressaopv 1.569e+02 7.328e-01 214.09
## LaboratorioPassante150meshhmi 1 2.504e+00 1.438e-01 17.42
## MoinhoCaixaDescargaCaixaABombaLigado 1 9.078e+00 3.564e-01 25.48
## MoinhoCaixaDescargaCaixaANivelmodo 1 -3.307e+01 4.450e-01 -74.32
## MoinhoCaixaDescargaCaixaRNivelmodo 1 1.259e+01 2.005e-01 62.79
## MoinhoHidrociclonesDensidadeLido 1 2.032e+00 1.496e-01 13.58
## MoinhoKnelsonBP04ALigado 1 3.543e+00 2.766e-01 12.81
## MoinhoKnelsonBP04RLigado 1 1.984e+01 3.097e-01 64.06
## Lag 9.769e-01 6.873e-04 1421.38
## Pr(>|t|)
## (Intercept) <2e-16 ***
## MoinhoAlimentacaoTaxaMineriomv <2e-16 ***
## MoinhoAlimentacaoTaxaMineriopv <2e-16 ***
## MoinhoAlimentacaoVazaoAguapv <2e-16 ***
## MoinhoCaixaDescargaCaixaABombaRotacaomv <2e-16 ***
## MoinhoCaixaDescargaCaixaANivelpv <2e-16 ***
## MoinhoCaixaDescargaCaixaRNivelpv <2e-16 ***
## MoinhoCaixaDescargaVazaoAguamv <2e-16 ***
## MoinhoCaixaDescargaVazaoAguapv <2e-16 ***
## MoinhoHidrociclonesDensidadepv <2e-16 ***
## MoinhoHidrociclonesPressaopv <2e-16 ***
## LaboratorioPassante150meshhmi 1 <2e-16 ***
## MoinhoCaixaDescargaCaixaABombaLigado 1 <2e-16 ***
## MoinhoCaixaDescargaCaixaANivelmodo 1 <2e-16 ***
## MoinhoCaixaDescargaCaixaRNivelmodo 1 <2e-16 ***
## MoinhoHidrociclonesDensidadeLido 1 <2e-16 ***
## MoinhoKnelsonBP04ALigado 1 <2e-16 ***
## MoinhoKnelsonBP04RLigado 1 <2e-16 ***
## Lag <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.67 on 98363 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.9729, Adjusted R-squared: 0.9729
## F-statistic: 1.962e+05 on 18 and 98363 DF, p-value: < 2.2e-16
##
## Call:
## glm(formula = Controle ~ MoinhoAlimentacaoTaxaMineriomv + MoinhoAlimentacaoTaxaMineriopv +
## MoinhoAlimentacaoVazaoAguapv + MoinhoCaixaDescargaCaixaABombaRotacaomv +
## MoinhoCaixaDescargaCaixaRNivelpv + MoinhoCaixaDescargaVazaoAguamv +
## MoinhoCaixaDescargaVazaoAguapv + MoinhoBombaDePocoLigada +
## MoinhoCaixaDescargaCaixaRBombaLigado + MoinhoCaixaDescargaCaixaRNivelmodo,
## family = binomial("logit"), data = df[train, -c(1, 2)])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -3.5017 0.0946 0.1074 0.1329 2.0193
##
## Coefficients:
## Estimate Std. Error z value
## (Intercept) 2.208352 0.729338 3.028
## MoinhoAlimentacaoTaxaMineriomv -0.069688 0.010375 -6.717
## MoinhoAlimentacaoTaxaMineriopv 0.024903 0.001312 18.980
## MoinhoAlimentacaoVazaoAguapv 0.026333 0.006615 3.981
## MoinhoCaixaDescargaCaixaABombaRotacaomv -0.030674 0.010322 -2.972
## MoinhoCaixaDescargaCaixaRNivelpv 0.023062 0.002726 8.460
## MoinhoCaixaDescargaVazaoAguamv -0.006042 0.001486 -4.066
## MoinhoCaixaDescargaVazaoAguapv 0.015392 0.001001 15.371
## MoinhoBombaDePocoLigada 1 0.365921 0.116044 3.153
## MoinhoCaixaDescargaCaixaRBombaLigado 1 -1.389542 0.156057 -8.904
## MoinhoCaixaDescargaCaixaRNivelmodo 1 0.668850 0.130554 5.123
## Pr(>|z|)
## (Intercept) 0.00246 **
## MoinhoAlimentacaoTaxaMineriomv 1.86e-11 ***
## MoinhoAlimentacaoTaxaMineriopv < 2e-16 ***
## MoinhoAlimentacaoVazaoAguapv 6.86e-05 ***
## MoinhoCaixaDescargaCaixaABombaRotacaomv 0.00296 **
## MoinhoCaixaDescargaCaixaRNivelpv < 2e-16 ***
## MoinhoCaixaDescargaVazaoAguamv 4.79e-05 ***
## MoinhoCaixaDescargaVazaoAguapv < 2e-16 ***
## MoinhoBombaDePocoLigada 1 0.00161 **
## MoinhoCaixaDescargaCaixaRBombaLigado 1 < 2e-16 ***
## MoinhoCaixaDescargaCaixaRNivelmodo 1 3.00e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 5325.1 on 32793 degrees of freedom
## Residual deviance: 3773.0 on 32783 degrees of freedom
## AIC: 3795
##
## Number of Fisher Scoring iterations: 7
## Value
## sensitivity 0.8272461
## specificity 0.6820000
## cutoff 0.9887848