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.
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