How can you train a MultinomialNB model for document classification with Scikit-learn and improve its performance

Question

With the help of code can i know How can you train a MultinomialNB model for document classification with Scikit-learn and improve its performance?

Answer 1

MultinomialNB in Scikit-learn is effective for document classification by modeling word frequencies, and performance can be improved through techniques like TF-IDF transformation and hyperparameter tuning.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Uses TF-IDF to convert text data into numerical features while reducing noise.
• Applies the MultinomialNB classifier with Laplace smoothing (alpha).
• Evaluates model performance with a classification report.

Hence, training a MultinomialNB model with TF-IDF transformation and proper hyperparameter tuning significantly enhances document classification accuracy and robustness.