Decision Tree Classifier for Social Network Ads

This repository implements a Decision Tree Classifier to predict user behavior based on age and estimated salary using the Social Network Ads dataset. The results are visualized for both the training and test sets.

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Table of Contents

• About the Project
• Technologies Used
• Setup
• Code Overview
• Results
• License

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About the Project

The objective is to classify users as potential buyers or not based on their age and estimated salary using a Decision Tree Classifier. The dataset is split into training and test sets, scaled, and then passed through the model. Visualizations are generated to interpret the classifier's decision boundaries.

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Technologies Used

This project uses the following technologies and libraries:

• Python: Programming language
• NumPy: Numerical computations
• Pandas: Data manipulation and analysis
• Matplotlib: Data visualization
• Scikit-learn: Machine learning algorithms

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Setup

Prerequisites

Ensure Python is installed. Recommended version: Python 3.8+.

Install the required libraries:

pip install numpy pandas matplotlib scikit-learn