Emotion-Classification

This project focuses on classification of textual data used to express emotion of a person. Our project tries to solve an NLP problem by designing an efficient machine learning model written in python to be able to distinguish these different emotions expressed. We used five machine learning models: Logistic Regression, Naïve Bayes, Random Forest, Feed Forward Neural Network and Bidirectional LSTM recurrent Neural Network to achieve this goal. We identified it as the best performing model based on F-1 score for all the classes.