https://github.com/ebadshabbir/naive_bayes_classification-gaussain-

A Python project that applies Naive Bayes classification to predict user purchases based on age and salary using the Social Network Ads dataset. The project includes data preprocessing, model training, prediction, and visualization of decision boundaries for both training and test datasets.
https://github.com/ebadshabbir/naive_bayes_classification-gaussain-

classification gaussian jupyter-notebook machine-learning matplotlib-pyplot naive-bayes-classifier numpy pandas python

Last synced: 17 days ago
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A Python project that applies Naive Bayes classification to predict user purchases based on age and salary using the Social Network Ads dataset. The project includes data preprocessing, model training, prediction, and visualization of decision boundaries for both training and test datasets.

• Host: GitHub
• URL: https://github.com/ebadshabbir/naive_bayes_classification-gaussain-
• Owner: EbadShabbir
• Created: 2024-10-30T10:12:41.000Z (18 days ago)
• Default Branch: main
• Last Pushed: 2024-10-30T10:17:30.000Z (18 days ago)
• Last Synced: 2024-10-30T11:24:33.220Z (18 days ago)
• Topics: classification, gaussian, jupyter-notebook, machine-learning, matplotlib-pyplot, naive-bayes-classifier, numpy, pandas, python
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/code/ebadshabbir/naive-bayes-classfication?scriptVersionId=2
• Size: 63.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Naive Bayes Classification on Social Network Ads Dataset

This project demonstrates a Naive Bayes classification model implemented in Python to predict user purchases based on their age and estimated salary, using data from the **Social Network Ads** dataset.

## Table of Contents

- [Project Overview](#project-overview)

- [Dataset](#dataset)

- [Installation](#installation)

- [Project Structure](#project-structure)

- [Usage](#usage)

- [Results](#results)

- [Contributing](#contributing)

- [License](#license)

## Project Overview

This project uses a Naive Bayes classifier to analyze and predict purchasing behavior. Key steps include data preprocessing, feature scaling, model training, and visualizing decision boundaries for both training and test sets.

## Dataset

The dataset used in this project is the **Social Network Ads** dataset, which includes information about user age, estimated salary, and whether or not they purchased a product. You can download the dataset from [Kaggle](https://www.kaggle.com) and place it in your project directory under the path: `input/social-network-adslogistic-regressionbinomial/Social Network Ads.csv`.

### Features:

- **Age**: Age of the user

- **Estimated Salary**: Salary estimation of the user

### Target:

- **Purchased**: Whether the user purchased the product (0 = No, 1 = Yes)

## Installation

1. Clone this repository:

   ```bash

   git clone https://github.com/EbadShabbi/Naive_Bayes_classification-gaussain.git

   cd Naive_Bayes_classification-gaussain