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Predicting whether a movie review is positive or negative - using SVC - 84.4% accuracy

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Movie Reviews Sentiment Analysis

  • Dataset containing different movie reviews.
  • Predicting whether a movie review is positive or negative.
  • Used NLTK library for data cleaning.
  • Used Classifiers such as Naive Bayes Classifier, Support Vector Classifier and Random Forest Classifier for training and testing data.
  • Attaining maximum accuracy of 84.4% using Support Vector Classifier.

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Predicting whether a movie review is positive or negative - using SVC - 84.4% accuracy

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