Build a Text Classifier with Naive Bayes
A visual walkthrough of gathering, preprocessing, training, and evaluating text for sentiment classification.
Article
Text classification turns documents into useful categories. This example builds a positive, negative, or neutral sentiment classifier using a Naive Bayes model.
The workflow covers data gathering, preprocessing, feature extraction, partitioning, model training, and evaluation.
Visual story
