A native implementation of the Multinomial Naive Bayes algorithm.
A native implementation of the Multinomial Naive Bayes algorithm.
Naive Bayes is a popular algorithm for text classification. It is a probabilistic classifier, which tells us the probability of the observation being in the class.
The multinomial Naive Bayes classifier is suitable for classification with discrete features (e.g., word counts for text classification).
Our implementation contains the fit and predict methods. Also methods for generating vocabs, cleaning documents and reading our data.
More information can be found at: https://medium.com/softup-technologies/building-a-ml-model-that-predicts-news-category-given-a-news-title-65c74867d876.