Naive-Bayes-Classifier

CONTENTS OF THIS FILE

• Description
• Requirements
• Installation
• Directory Structure
• Usage
• Credits

Description

Naive bayes classifier uses baye's theorem to classify samples with strong (naïve) independence assumptions between the features. Gaussian naive bayes is an extension of naive bayes classifier, which deals with points modelled with guassian distribution.

Requirements

1. Python 3
2. Numpy
3. Sci-kit Learn
4. Pandas
5. Matplotlib
6. Jupyter Notebook

Installation

1. Python

Step 1: Visit and download Python from https://www.python.org/downloads/ Step 2: Install and add Python to path

2. Numpy

In command prompt

pip install numpy

3. Sci-kit Learn

In command prompt

pip install sklearn

4. Pandas

In command prompt

pip install pandas

5. Matplotlib

In command prompt

pip install matplotlib

6. Jupyter

In command prompt

pip install jupyterlab

For conda users

conda install -c conda-forge jupyterlab

To start Jupyter type

jupyter notebook

Directory Structure

.
├── src                     # Source files
│   ├── naive_bayes.ipynb   # Jupyter Notebook
├── LICENSE
└── README.md

Usage

The jupyter notebook (source code) is present in the 'src' folder. An example containing two gaussian distributions have been provided in the 'main' (inside the code).