Naive-Bayes-Classification-from-Scratch

Naive Bayes is a statistical classification technique based on Bayes Theorem. It is one of the simplest supervised learning algorithms.

Naive Bayes classifiers have high accuracy and speed on large datasets.

It is not a single algorithm but a family of algorithms where all of them shares a common principle, i.e every pair of features being classified is independent of each other.

Formula for Gaussain Naive Bayes.

Documentation of GaussianNB:

https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html

Evaluation of the Model:

            precision    recall  f1-score   support
      0       0.91      0.95      0.93        21
      1       0.94      0.79      0.86        19
      2       0.88      1.00      0.93        14
avg / total   0.91      0.91      0.91        54

Accuracy: 0.90