Data

Model

Normalization

None

Z-standard

Min-Max

MaxAbs (−1, 1)

Quantile Transform

Quantile Normalize

Bivariate Normal - Continuous Target

Linear

Type of Loss

MSE

MSE

MSE

MSE

MSE

MSE

Total Loss

0.338

200,151.804

8,999,347.482

2,146,481,764.484

2,247,609.346

0.344

Bias

0.335

200,151.449

8,999,335.213

2,146,478,729.725

2,247,069.765

0.338

Variance

0.003

0.355

12.269

12.269

539.581

0.006

Noise

0.000

0.000

0.000

3022.490

0.000

0.000

Variance-Bias Ratio

0.008

0.000

0.000

0.000

0.000

0.019

Percent Change from Raw

~

59,281,297.280

2,665,441,848.182

635,748,573,177.009

665,700,710.123

101.929

Decision Tree

Total Loss

0.748

114.588

114.588

114.588

114.588

0.589

Bias

0.444

111.856

111.856

111.856

111.856

0.338

Variance

0.304

2.731

2.731

2.731

2.731

0.251

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.685

0.024

0.024

0.024

0.024

0.742

Percent Change from Raw

~

15,311.228

15,311.228

15,311.228

15,311.228

78.694

Random Forest

Total Loss

2.809

22.970

22.970

22.970

22.970

2.812

Bias

2.425

22.501

22.501

22.501

22.501

2.427

Variance

0.385

0.469

0.469

0.469

0.469

0.385

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance-Bias Ratio

0.159

0.021

0.021

0.021

0.021

0.158