KNN Iris Classifier

This project demonstrates a K-Nearest Neighbors (KNN) classifier for the Iris dataset. The application allows users to:

1. Tune the hyperparameter k (number of neighbors).
2. Evaluate the model's performance (accuracy and balanced accuracy).
3. Predict the iris species based on user-provided input.

Features

• Hyperparameter tuning for KNN (k selection).
• Model training and evaluation.
• Console-based user input for custom predictions.
• Performance metrics: Accuracy and Balanced Accuracy.

Requirements

Ensure you have the following installed:

• Python 3.x
• pandas
• scikit-learn

Setup

1. Clone the repository:

   git clone https://github.com/yourusername/CAU-AID-Class.git

2. Navigate to the project directory:

   cd CAU-AID-Class

3. Install required libraries:

   pip install pandas scikit-learn

4. Ensure the iris.csv dataset is available in the project directory.