Once the Model is built we want to check its performance, i did the following
- Predicted it on training set.
- Compute confusion matrix and ROC curve on training set.
- Predicted on test set
- Computed Confusion Matrix and ROC Curve on test set.
I want to know is it a right way and what more precise can be done?
I am using Decision Tress Random Forest SVM Both Linear Radial Naive Bayeian
Logistic regression and Neural Network. Do all of them have different