This project involves comparing the accuracy of different machine learning models and vectorization techniques for a text classification task.
The models used in this project include:
- Multinomial Naive Bayes
- Logistic Regression
- Linear Support Vector Machine
Each model is tested with three different vectorization techniques:
- Bag of Words
- TF-IDF
- Hashing
To run the project, execute the main script in your Python environment. The script will train the models on the training data, evaluate them on the test data, and display the results in a bar chart.