Sentiment Analysis using Ensemble Classification Technique

Sentiment Analysis of Twitter data is a way to predict the emotional tone of the tweets. There are various challenges faced in the process of predicting the correct sentiment of the tweets. The data is pre-processed using the (Term Frequency-Inverse Document Frequency Vectorizer) TF -IDF Vectorizer to extract the features of the tweets. Afterwards various classification techniques like Random Forest, Support Vector Machine, Logistic Regression, Naïve Bayes, and SGD Classifier are used to classify the data. After classification, the models are passed into Voting Classification technique of Ensemble Classification methodology.