K-Nearest Neighbors (K-NN) Classification

This repository contains an implementation of the K-Nearest Neighbors (K-NN) algorithm for classifying users based on their age and estimated salary. The dataset used is the "Social Network Ads" dataset.

Overview

The K-NN algorithm is a simple, non-parametric classification algorithm that works by finding the majority class among a query point's nearest neighbors. In this project, we:

• Load and preprocess the dataset
• Train a K-NN model
• Evaluate the model using a confusion matrix
• Visualize decision boundaries for both the training and test datasets

Prerequisites

Ensure you have the following libraries installed:

```bash
pip install numpy pandas matplotlib scikit-learn

Cloning the repository

git clone https:/EbadShabbir/github.com//knn-classification.git
cd knn-classification