ExcelR Data Science Assignment No 12
- Naive Bayes algorithm is a supervised learning algorithm, which is based on Bayes theorem and used for solving classification problems.
- It is mainly used in text classification that includes a high-dimensional training dataset.
- Naive Bayes Classifier is one of the simple and most effective Classification algorithms which helps in building the fast machine learning models that can make quick predictions.
- It is a probabilistic classifier, which means it predicts on the basis of the probability of an object.
- Some popular examples of Naïve Bayes Algorithm are spam filtration, Sentimental analysis, and classifying articles.
- GaussianNB → When you have continuous features.
- CategoricalNB → When you have categorical data.
- MultinomialNB → Applied to text data.
- Prepare a classification model using Naive Bayes for salary data