Decision Tree

Total Loss

1.869

1.801

1.801

1.802

1.801

2.065

Bias

1.126

1.428

1.428

1.429

1.428

1.173

Variance

0.743

0.373

0.373

0.373

0.373

0.892

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.660

0.261

0.261

0.261

0.261

0.760

Percent Change from Raw

~

96.319

96.319

96.371

96.319

110.450

Random Forest

Total Loss

1.564

1.125

1.125

1.125

1.125

1.564

Bias

1.369

0.980

0.980

0.980

0.980

1.370

Variance

0.195

0.145

0.145

0.145

0.145

0.194

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.142

0.148

0.148

0.148

0.148

0.142

Percent Change from Raw

~

71.964

71.964

71.964

71.964

100.059

SVM

Total Loss

1.676

1.324

1.443

1.886

1.341

1.700

Bias

1.528

1.091

1.192

1.805

1.104

1.556

Variance

0.148

0.233

0.252

0.252

0.237

0.143

Noise

0.000

0.000

0.000

0.171

0.000

0.000

Variance-Bias Ratio

0.097

0.213

0.211

0.139

0.214

0.092

Percent Change from Raw

~

78.974

86.122

112.515

80.023

101.403

Gradient Boosting

Total Loss

1.561

1.167

1.167

1.167

1.167

1.550

Bias

1.325

0.943

0.943

0.943

0.943

1.319

Variance

0.235

0.224

0.224

0.224

0.224

0.231

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.178

0.237

0.237

0.237

0.237

0.175

Percent Change from Raw

~

74.795

74.795

74.791

74.795

99.310

Neural Network

Total Loss

1.501

50.236

2611.864

553,224.671

740.072

1.496

Bias

1.253

25.275

1286.970

257,374.377

412.057

1.267

Variance

0.248

24.961

1324.894

1324.894

328.015

0.229

Noise

0.000

0.000

0.000

294,525.400

0.000

0.000

Variance-Bias Ratio

0.198

0.988

1.029

0.005

0.796

0.181

Percent Change from Raw

~

3346.523

173,990.881

36,853,390.488

49,300.337

99.642