Gaussian Naive Bayes

Implement Gaussian Naive Bayes classifier using scikit-learn on iris dataset.

Step 01: Import the library

Imported various modules like datasets, mertics, and GaussianNB from differnt libraries.

Step 02: Setup the Data

Here used datasets to load the inbuilt iris dataset and created objects X and y to store the data and the target value respectively.

Step 03: Model and its Score

• Take GaussianNB as a Machine Learning model to fit the data.

• Then predicted the output by passing X_test and also stored real target in expected_y.

• then printed classification report and confusion matrix for the classifier.