Analysed Tweets and classified it into categories- positive, negative, neutral.

• Imported dataset
• Analysed data
• Used Count Vectorizer
• Prediction using SVC
• Prediction using Random Forest
• Prediction using Multinomial Naive Bayes
• Applied Grid Search Cross Validation
• Comparison between various classifier

• SVC : 0.633
• Random Forest : 0.723
• Multinomial Naive Bayes : 0.755

Best accuracy comes from Multinomial Naive Bayes.

git clone https://github.com/wikiabhi/Twitter-Sentiment-Analysis.git

MIT License Copyright (c) 2018 Abhishek