This project implements a sentiment analysis system that classifies movie reviews as either positive or negative. It leverages the Naive Bayes classification algorithm, commonly used for text classification tasks.
The project uses the nltk library to load and preprocess the IMDb movie reviews dataset and scikit-learn to build, train, and evaluate the model.
- Loads IMDb movie reviews dataset using NLTK.
- Preprocesses text data and converts it into feature vectors using
CountVectorizer. - Trains a Naive Bayes classifier for sentiment analysis.
- Evaluates model performance using accuracy score and classification report.
- Predicts sentiment for user-inputted movie reviews.
Make sure you have the following installed before running the project:
- Python 3.6 or later
- pip (Python package manager)
You can check your Python version with:
python3 --version