Sentiment analysis based on movies reviews.
The main goal of this project is to predict the sentiments of sentences.
We work with IMDB movies reviews dataset. Movies are rated from 1 to 10. We consider only the reviews with rating 1 (the worst ones) and 10 (the best ones).
The assumption is that movies with rating 1 have negative sentiment and movies with rating 10 have a positive sentiment.
- Python - version 3.7.3
- numpy
- pandas
- matplotlib
- seaborn
- sklearn
- nltk
- scipy
- glob
- re
- cvxopt
- tqdm
- Accuracies below are measured on test data.
- Baseline accuracy: 52%.
- Naive Bayes: 89.95%.
- Logistic Regression: 89.92%.
- SVM: 92.16%.
- Heuristic Naive Bayes: 90.32%.
Project is: finished,
Machine Learning class.
Created by @TheFebrin, @MatMarkiewicz and @gKlocek
