+ Fold1.Rep1: mtry=2
- Fold1.Rep1: mtry=2
+ Fold1.Rep1: mtry=8
- Fold1.Rep1: mtry=8
+ Fold2.Rep1: mtry=2
- Fold2.Rep1: mtry=2
+ Fold2.Rep1: mtry=8
- Fold2.Rep1: mtry=8
+ Fold3.Rep1: mtry=2
- Fold3.Rep1: mtry=2
+ Fold3.Rep1: mtry=8
- Fold3.Rep1: mtry=8
+ Fold1.Rep2: mtry=2
- Fold1.Rep2: mtry=2
+ Fold1.Rep2: mtry=8
- Fold1.Rep2: mtry=8
+ Fold2.Rep2: mtry=2
- Fold2.Rep2: mtry=2
+ Fold2.Rep2: mtry=8
- Fold2.Rep2: mtry=8
+ Fold3.Rep2: mtry=2
- Fold3.Rep2: mtry=2
+ Fold3.Rep2: mtry=8
- Fold3.Rep2: mtry=8
+ Fold1.Rep3: mtry=2
- Fold1.Rep3: mtry=2
+ Fold1.Rep3: mtry=8
- Fold1.Rep3: mtry=8
+ Fold2.Rep3: mtry=2
- Fold2.Rep3: mtry=2
+ Fold2.Rep3: mtry=8
- Fold2.Rep3: mtry=8
+ Fold3.Rep3: mtry=2
- Fold3.Rep3: mtry=2
+ Fold3.Rep3: mtry=8
- Fold3.Rep3: mtry=8
Aggregating results
Selecting tuning parameters
Fitting mtry = 2 on full training set
Conditional Inference Random Forest
768 samples
8 predictor
2 classes: 'neg', 'pos'
Pre-processing: centered (8), scaled (8)
Resampling: Cross-Validated (3 fold, repeated 3 times)
Summary of sample sizes: 511, 512, 513, 511, 513, 512, ...
Resampling results across tuning parameters:
mtry Accuracy Kappa
2 0.7686600 0.4535750
8 0.7591129 0.4478574
Accuracy was used to select the optimal model using the largest value.
The final value used for the model was mtry = 2.
+ Fold1.Rep1: mtry=2, coefReg=0.01, coefImp=0
- Fold1.Rep1: mtry=2, coefReg=0.01, coefImp=0
+ Fold1.Rep1: mtry=8, coefReg=0.01, coefImp=0
- Fold1.Rep1: mtry=8, coefReg=0.01, coefImp=0
+ Fold1.Rep1: mtry=2, coefReg=1.00, coefImp=0
- Fold1.Rep1: mtry=2, coefReg=1.00, coefImp=0
+ Fold1.Rep1: mtry=8, coefReg=1.00, coefImp=0
- Fold1.Rep1: mtry=8, coefReg=1.00, coefImp=0
+ Fold1.Rep1: mtry=2, coefReg=0.01, coefImp=1
- Fold1.Rep1: mtry=2, coefReg=0.01, coefImp=1
+ Fold1.Rep1: mtry=8, coefReg=0.01, coefImp=1
- Fold1.Rep1: mtry=8, coefReg=0.01, coefImp=1
+ Fold1.Rep1: mtry=2, coefReg=1.00, coefImp=1
- Fold1.Rep1: mtry=2, coefReg=1.00, coefImp=1
+ Fold1.Rep1: mtry=8, coefReg=1.00, coefImp=1
- Fold1.Rep1: mtry=8, coefReg=1.00, coefImp=1
+ Fold2.Rep1: mtry=2, coefReg=0.01, coefImp=0
- Fold2.Rep1: mtry=2, coefReg=0.01, coefImp=0
+ Fold2.Rep1: mtry=8, coefReg=0.01, coefImp=0
- Fold2.Rep1: mtry=8, coefReg=0.01, coefImp=0
+ Fold2.Rep1: mtry=2, coefReg=1.00, coefImp=0
- Fold2.Rep1: mtry=2, coefReg=1.00, coefImp=0
+ Fold2.Rep1: mtry=8, coefReg=1.00, coefImp=0
- Fold2.Rep1: mtry=8, coefReg=1.00, coefImp=0
+ Fold2.Rep1: mtry=2, coefReg=0.01, coefImp=1
- Fold2.Rep1: mtry=2, coefReg=0.01, coefImp=1
+ Fold2.Rep1: mtry=8, coefReg=0.01, coefImp=1
- Fold2.Rep1: mtry=8, coefReg=0.01, coefImp=1
+ Fold2.Rep1: mtry=2, coefReg=1.00, coefImp=1
- Fold2.Rep1: mtry=2, coefReg=1.00, coefImp=1
+ Fold2.Rep1: mtry=8, coefReg=1.00, coefImp=1
- Fold2.Rep1: mtry=8, coefReg=1.00, coefImp=1
+ Fold3.Rep1: mtry=2, coefReg=0.01, coefImp=0
- Fold3.Rep1: mtry=2, coefReg=0.01, coefImp=0
+ Fold3.Rep1: mtry=8, coefReg=0.01, coefImp=0
- Fold3.Rep1: mtry=8, coefReg=0.01, coefImp=0
+ Fold3.Rep1: mtry=2, coefReg=1.00, coefImp=0
- Fold3.Rep1: mtry=2, coefReg=1.00, coefImp=0
+ Fold3.Rep1: mtry=8, coefReg=1.00, coefImp=0
- Fold3.Rep1: mtry=8, coefReg=1.00, coefImp=0
+ Fold3.Rep1: mtry=2, coefReg=0.01, coefImp=1
- Fold3.Rep1: mtry=2, coefReg=0.01, coefImp=1
+ Fold3.Rep1: mtry=8, coefReg=0.01, coefImp=1
- Fold3.Rep1: mtry=8, coefReg=0.01, coefImp=1
+ Fold3.Rep1: mtry=2, coefReg=1.00, coefImp=1
- Fold3.Rep1: mtry=2, coefReg=1.00, coefImp=1
+ Fold3.Rep1: mtry=8, coefReg=1.00, coefImp=1
- Fold3.Rep1: mtry=8, coefReg=1.00, coefImp=1
+ Fold1.Rep2: mtry=2, coefReg=0.01, coefImp=0
- Fold1.Rep2: mtry=2, coefReg=0.01, coefImp=0
+ Fold1.Rep2: mtry=8, coefReg=0.01, coefImp=0
- Fold1.Rep2: mtry=8, coefReg=0.01, coefImp=0
+ Fold1.Rep2: mtry=2, coefReg=1.00, coefImp=0
- Fold1.Rep2: mtry=2, coefReg=1.00, coefImp=0
+ Fold1.Rep2: mtry=8, coefReg=1.00, coefImp=0
- Fold1.Rep2: mtry=8, coefReg=1.00, coefImp=0
+ Fold1.Rep2: mtry=2, coefReg=0.01, coefImp=1
- Fold1.Rep2: mtry=2, coefReg=0.01, coefImp=1
+ Fold1.Rep2: mtry=8, coefReg=0.01, coefImp=1
- Fold1.Rep2: mtry=8, coefReg=0.01, coefImp=1
+ Fold1.Rep2: mtry=2, coefReg=1.00, coefImp=1
- Fold1.Rep2: mtry=2, coefReg=1.00, coefImp=1
+ Fold1.Rep2: mtry=8, coefReg=1.00, coefImp=1
- Fold1.Rep2: mtry=8, coefReg=1.00, coefImp=1
+ Fold2.Rep2: mtry=2, coefReg=0.01, coefImp=0
- Fold2.Rep2: mtry=2, coefReg=0.01, coefImp=0
+ Fold2.Rep2: mtry=8, coefReg=0.01, coefImp=0
- Fold2.Rep2: mtry=8, coefReg=0.01, coefImp=0
+ Fold2.Rep2: mtry=2, coefReg=1.00, coefImp=0
- Fold2.Rep2: mtry=2, coefReg=1.00, coefImp=0
+ Fold2.Rep2: mtry=8, coefReg=1.00, coefImp=0
- Fold2.Rep2: mtry=8, coefReg=1.00, coefImp=0
+ Fold2.Rep2: mtry=2, coefReg=0.01, coefImp=1
- Fold2.Rep2: mtry=2, coefReg=0.01, coefImp=1
+ Fold2.Rep2: mtry=8, coefReg=0.01, coefImp=1
- Fold2.Rep2: mtry=8, coefReg=0.01, coefImp=1
+ Fold2.Rep2: mtry=2, coefReg=1.00, coefImp=1
- Fold2.Rep2: mtry=2, coefReg=1.00, coefImp=1
+ Fold2.Rep2: mtry=8, coefReg=1.00, coefImp=1
- Fold2.Rep2: mtry=8, coefReg=1.00, coefImp=1
+ Fold3.Rep2: mtry=2, coefReg=0.01, coefImp=0
- Fold3.Rep2: mtry=2, coefReg=0.01, coefImp=0
+ Fold3.Rep2: mtry=8, coefReg=0.01, coefImp=0
- Fold3.Rep2: mtry=8, coefReg=0.01, coefImp=0
+ Fold3.Rep2: mtry=2, coefReg=1.00, coefImp=0
- Fold3.Rep2: mtry=2, coefReg=1.00, coefImp=0
+ Fold3.Rep2: mtry=8, coefReg=1.00, coefImp=0
- Fold3.Rep2: mtry=8, coefReg=1.00, coefImp=0
+ Fold3.Rep2: mtry=2, coefReg=0.01, coefImp=1
- Fold3.Rep2: mtry=2, coefReg=0.01, coefImp=1
+ Fold3.Rep2: mtry=8, coefReg=0.01, coefImp=1
- Fold3.Rep2: mtry=8, coefReg=0.01, coefImp=1
+ Fold3.Rep2: mtry=2, coefReg=1.00, coefImp=1
- Fold3.Rep2: mtry=2, coefReg=1.00, coefImp=1
+ Fold3.Rep2: mtry=8, coefReg=1.00, coefImp=1
- Fold3.Rep2: mtry=8, coefReg=1.00, coefImp=1
+ Fold1.Rep3: mtry=2, coefReg=0.01, coefImp=0
- Fold1.Rep3: mtry=2, coefReg=0.01, coefImp=0
+ Fold1.Rep3: mtry=8, coefReg=0.01, coefImp=0
- Fold1.Rep3: mtry=8, coefReg=0.01, coefImp=0
+ Fold1.Rep3: mtry=2, coefReg=1.00, coefImp=0
- Fold1.Rep3: mtry=2, coefReg=1.00, coefImp=0
+ Fold1.Rep3: mtry=8, coefReg=1.00, coefImp=0
- Fold1.Rep3: mtry=8, coefReg=1.00, coefImp=0
+ Fold1.Rep3: mtry=2, coefReg=0.01, coefImp=1
- Fold1.Rep3: mtry=2, coefReg=0.01, coefImp=1
+ Fold1.Rep3: mtry=8, coefReg=0.01, coefImp=1
- Fold1.Rep3: mtry=8, coefReg=0.01, coefImp=1
+ Fold1.Rep3: mtry=2, coefReg=1.00, coefImp=1
- Fold1.Rep3: mtry=2, coefReg=1.00, coefImp=1
+ Fold1.Rep3: mtry=8, coefReg=1.00, coefImp=1
- Fold1.Rep3: mtry=8, coefReg=1.00, coefImp=1
+ Fold2.Rep3: mtry=2, coefReg=0.01, coefImp=0
- Fold2.Rep3: mtry=2, coefReg=0.01, coefImp=0
+ Fold2.Rep3: mtry=8, coefReg=0.01, coefImp=0
- Fold2.Rep3: mtry=8, coefReg=0.01, coefImp=0
+ Fold2.Rep3: mtry=2, coefReg=1.00, coefImp=0
- Fold2.Rep3: mtry=2, coefReg=1.00, coefImp=0
+ Fold2.Rep3: mtry=8, coefReg=1.00, coefImp=0
- Fold2.Rep3: mtry=8, coefReg=1.00, coefImp=0
+ Fold2.Rep3: mtry=2, coefReg=0.01, coefImp=1
- Fold2.Rep3: mtry=2, coefReg=0.01, coefImp=1
+ Fold2.Rep3: mtry=8, coefReg=0.01, coefImp=1
- Fold2.Rep3: mtry=8, coefReg=0.01, coefImp=1
+ Fold2.Rep3: mtry=2, coefReg=1.00, coefImp=1
- Fold2.Rep3: mtry=2, coefReg=1.00, coefImp=1
+ Fold2.Rep3: mtry=8, coefReg=1.00, coefImp=1
- Fold2.Rep3: mtry=8, coefReg=1.00, coefImp=1
+ Fold3.Rep3: mtry=2, coefReg=0.01, coefImp=0
- Fold3.Rep3: mtry=2, coefReg=0.01, coefImp=0
+ Fold3.Rep3: mtry=8, coefReg=0.01, coefImp=0
- Fold3.Rep3: mtry=8, coefReg=0.01, coefImp=0
+ Fold3.Rep3: mtry=2, coefReg=1.00, coefImp=0
- Fold3.Rep3: mtry=2, coefReg=1.00, coefImp=0
+ Fold3.Rep3: mtry=8, coefReg=1.00, coefImp=0
- Fold3.Rep3: mtry=8, coefReg=1.00, coefImp=0
+ Fold3.Rep3: mtry=2, coefReg=0.01, coefImp=1
- Fold3.Rep3: mtry=2, coefReg=0.01, coefImp=1
+ Fold3.Rep3: mtry=8, coefReg=0.01, coefImp=1
- Fold3.Rep3: mtry=8, coefReg=0.01, coefImp=1
+ Fold3.Rep3: mtry=2, coefReg=1.00, coefImp=1
- Fold3.Rep3: mtry=2, coefReg=1.00, coefImp=1
+ Fold3.Rep3: mtry=8, coefReg=1.00, coefImp=1
- Fold3.Rep3: mtry=8, coefReg=1.00, coefImp=1
Aggregating results
Selecting tuning parameters
Fitting mtry = 8, coefReg = 1, coefImp = 0 on full training set
Regularized Random Forest
768 samples
8 predictor
2 classes: 'neg', 'pos'
Pre-processing: centered (8), scaled (8)
Resampling: Cross-Validated (3 fold, repeated 3 times)
Summary of sample sizes: 511, 513, 512, 511, 512, 513, ...
Resampling results across tuning parameters:
mtry coefReg coefImp Accuracy Kappa
2 0.01 0 0.6979612 0.3109660
2 0.01 1 0.7356897 0.4016199
2 1.00 0 0.7561095 0.4473596
2 1.00 1 0.7257035 0.3835740
8 0.01 0 0.7183198 0.3607852
8 0.01 1 0.7257018 0.3804981
8 1.00 0 0.7565351 0.4484112
8 1.00 1 0.7235486 0.3759642
Accuracy was used to select the optimal model using the largest value.
The final values used for the model were mtry = 8, coefReg = 1 and coefImp = 0.