Neural Network
7000 samples
5 predictor
No pre-processing
Resampling: Bootstrapped (25 reps)
Summary of sample sizes: 7000, 7000, 7000, 7000, 7000, 7000, ...
Resampling results across tuning parameters:
size decay RMSE Rsquared RMSE SD Rsquared SD
2 0.001 0.06523965 0.5769124 0.002201100 0.02533697
2 0.010 0.06648973 0.5608278 0.002679545 0.02760100
2 0.100 0.06951389 0.5208065 0.002157327 0.02633275
3 0.001 0.06511631 0.5787308 0.002313365 0.02733156
3 0.010 0.06568067 0.5711052 0.002209810 0.02585617
3 0.100 0.06904968 0.5272302 0.002088746 0.02598566
5 0.001 0.06495730 0.5807438 0.002076235 0.02457236
5 0.010 0.06570316 0.5707927 0.002166298 0.02560607
5 0.100 0.06905890 0.5270862 0.002087202 0.02589815
RMSE was used to select the optimal model using the smallest value.
The final values used for the model were size = 5 and decay = 0.001.