Without PCA
Support Vector Machines with Radial Basis Function Kernel
9685 samples
4 predictor
No pre-processing
Resampling: Cross-Validated (10 fold)
Summary of sample sizes: 8717, 8715, 8718, 8717, 8715, 8716, ...
Resampling results across tuning parameters:
# Train the SVM model with the best parameters
C sigma RMSE Rsquared MAE
0.1 0.5 0.1489409 0.3791848 0.1152221
0.1 1.0 0.1496952 0.3715801 0.1160810
0.1 2.0 0.1518043 0.3528460 0.1183108
1.0 0.5 0.1492998 0.3810286 0.1149792
1.0 1.0 0.1508168 0.3700282 0.1161860
1.0 2.0 0.1532086 0.3523641 0.1184146
10.0 0.5 0.1515176 0.3683280 0.1165050
10.0 1.0 0.1563312 0.3389117 0.1205078
10.0 2.0 0.1634327 0.2997668 0.1269389
RMSE was used to select the optimal model using the smallest value.
The final values used for the model were sigma = 0.5 and C = 0.1.