Percent Change from Raw

~

1255.334

1255.334

1255.334

1255.334

100.000

SVM

Total Loss

468,652.034

468,824.111

468,659.254

468,659.354

468,687.960

468,652.034

Bias

467,902.232

468,167.990

467,974.616

467,974.484

467,999.280

467,902.232

Variance

749.803

656.121

684.638

684.638

688.680

749.803

Noise

0.000

0.000

0.000

0.232

0.000

0.000

Variance- Bias Ratio

0.002

0.001

0.001

0.001

0.001

0.002

Percent Change from Raw

~

100.037

100.002

100.002

100.008

100.000

Gradient Boosting

Total Loss

10,562.614

3,087,157.051

3,087,157.051

3,087,157.051

3,087,157.051

10,562.614

Bias

3,197.090

3,083,591.900

3,083,591.900

3,083,591.900

3,083,591.900

3197.090

Variance

7365.524

3565.151

3565.151

3565.151

3565.151

7365.524

Noise

0.000

0.000

0.000

0.000

0.000

0.000

Variance- Bias Ratio

2.304

0.001

0.001

0.001

0.001

2.304

Percent Change from Raw

~

29227.208

29227.208

29227.208

29227.208

100.000

Neural Network

Total Loss

0.175

304,375,382,136.401

3,627,820,444,148.760

3,635,081,654,196.280

3,635,123,003,365.700

0.175

Bias

0.174

304,375,382,127.117

3,627,820,444,038.680

3,635,081,654,084.160

3,635,121,483,216.140

0.174

Variance

0.001

9.284

110.079

110.079

1520149.555

0.001

Noise

0.000

0.000

0.000

2.041

0.005

0.000

Variance- Bias Ratio

0.007

0.000

0.000

0.000

0.000

0.007

Percent Change from Raw

~

173,769,104,867,507.000

2,071,136,984,781,720.000

2,075,282,438,206,230.000

2,075,306,044,609,960.000

99.994