Data division
The randomized data was grouped into training, testing and validation datasets. Training dataset was used to arrive at potentially predictive relations. It is a set of examples employed for learning, that is, to fit the parameters (that is, weights) of the classifier. A test dataset was used to evaluate the strength and utility of a predictive relationship, it is a set of examples used only to measure the performance (generalization) of a fully-specified classifier. So as to avoid overfitting, it was imperative to have a validation set in addition to training and testing sets.