At this point, we have trained five different models. The predictions are stored in two data frames, one for training and the other for the validation samples:
head(summary_models_train)
## ID_RSSD Default GLM RF GBM deep
## 4 37 0 0.0013554364 0 0.000005755001 0.000000018217172
## 21 242 0 0.0006967876 0 0.000005755001 0.000000002088871
## 38 279 0 0.0028306028 0 0.000005240935 0.000003555978680
## 52 354 0 0.0013898732 0 0.000005707480 0.000000782777042
## 78 457 0 0.0021731695 0 0.000005755001 0.000000012535539
## 81 505 0 0.0011344433 0 0.000005461855 0.000000012267744
## SVM
## 4 0.0006227083
## 21 0.0002813123
## 38 0.0010763298
## 52 0.0009740568
## 78 0.0021555739
## 81 0.0005557417
Let's summarize the accuracy of the previously trained models...
