Assignment12-Naive-Bayes

ExcelR Data Science Assignment No 12

Naive Bayes Algorithm :

• 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.

Each algorithm of Naive Bayes expects different types of data.

• GaussianNB → When you have continuous features.
• CategoricalNB → When you have categorical data.
• MultinomialNB → Applied to text data.

This assignment will study following Question :

1. Prepare a classification model using Naive Bayes for salary data