aligeekk / ensemble-classifier

Deep neural network classifier that uses auto-encoders for feature selection. The primary objective is to evaluate the performance difference between regular classification models with topic modeling and deep neural network with auto-encoders. Tools/technologies used: Scikit-learn, Python machine learning models, Keras

Ensemble-classifier

This project is about creating an ensemble deep neural network classifier that uses auto-encoders for feature selection. A detailed comparison is done between the regular classifiers (feature selection is done using LDA) and the deep neural classifiers. The primary objective is to evaluate the performance difference between regular classification models with topic modeling and deep neural network with auto-encoders. Tools/technologies used: Scikit-learn, Python machine learning models, Keras