Decision Tree

Total Loss

0.066

0.063

0.066

0.066

0.066

0.066

Bias

0.036

0.040

0.036

0.036

0.036

0.036

Variance

0.030

0.023

0.030

0.043

0.030

0.030

Noise

0.000

0.000

0.000

0.013

0.000

0.000

Variance-Bias Ratio

0.853

0.567

0.816

1.182

0.816

0.816

Percent Change from Raw

~

96.100

100.475

100.475

100.475

100.475

Random Forest

Total Loss

0.044

0.053

0.044

0.044

0.044

0.044

Bias

0.031

0.041

0.031

0.031

0.031

0.031

Variance

0.012

0.012

0.012

0.018

0.012

0.012

Noise

0.000

0.000

0.000

0.005

0.000

0.000

Variance-Bias Ratio

0.388

0.297

0.388

0.561

0.388

0.388

Percent Change from Raw

~

121.723

100.000

100.000

100.000

100.000

SVM

Total Loss

0.052

0.054

0.052

0.052

0.052

0.052

Bias

0.045

0.038

0.045

0.045

0.045

0.045

Variance

0.007

0.016

0.007

0.011

0.007

0.007

Noise

0.000

0.000

0.000

0.004

0.000

0.000

Variance-Bias Ratio

0.162

0.427

0.162

0.247

0.162

0.163

Percent Change from Raw

~

102.883

100.000

100.000

100.000

99.649

Gradient Boosting

Total Loss

0.056

0.058

0.056

0.056

0.056

0.056

Bias

0.033

0.039

0.033

0.033

0.033

0.033

Variance

0.022

0.019

0.022

0.032

0.022

0.022

Noise

0.000

0.000

0.000

0.009

0.000

0.000

Variance-Bias Ratio

0.668

0.472

0.668

0.949

0.668

0.668

Percent Change from Raw

~

103.490

100.000

100.000

100.000

100.000

Neural Network

Total Loss

0.059

0.079

0.059

0.059

0.059

0.058

Bias

0.045

0.059

0.045

0.045

0.045

0.044

Variance

0.014

0.021

0.014

0.020

0.014

0.014

Noise

0.000

0.000

0.000

0.006

0.000

0.000

Variance-Bias Ratio

0.312

0.353

0.312

0.442

0.312

0.307

Percent Change from Raw

~

134.324

100.000

100.000

100.000

98.049