This Github repository is about creating the K-Nearest Neighbor (KNN) algorithm from scratch. The code uses the iris dataset which is commonly used for testing machine learning algorithms.
- Clone this repository to your local machine using the command:
git clone https://github.com/sagarmk/knn-iris-classifier.git - Make sure you have Python and required libraries (csv, random, math, operator) installed on your machine.
- Navigate to the repository using the command line.
- Execute the code using the command
python main.py - The code will perform the following steps:
- Load the Iris dataset from the file 'iris.data'
- Split the dataset into training and testing sets using the split value (0.67)
- Train the KNN algorithm on the training set
- Use the trained algorithm to generate predictions on the test set
- Measure the accuracy of the predictions
- Display the accuracy and predictions.