Otto Kaggle challenge.

The objective is to build a predictive model which is able to distinguish between nine main product categories. The dataset provided has 93 features for more than 200,000 products. These programs build the following models:

Support Vector Machine and BaggingKnn

Boosting model: AdaBoost and Gradient Boosting

Neuronal networks: NN with 2 hidden layers for multliple labels clsssification (DropoutNN2hl function) and NN dropout NN with 2 hidden layers (NNSoftMax function)

Ensemble models in BlendingModel.