K-Nearest-Neighbours-Classifier

An implementation of K-Nearest Neighbours Classification from scratch without using the scikit-learn's KNNClassifier function.

Introduction

K-Nearest Neighbours Classifier is a lazy classification and regression method which is usually used in pattern recognition. It is a classic example of instance-based learning or lazy learning. Here we have done a simple KNNClassifier implementation on the famous Breast Cancer Wisconsin Dataset. Data processing has already been conducted which included basic data manipulation.

How To Run ?

1. Simply run the knnearestclassifier.py on your command line.
2. Ensure you have the necessary libraries installed on your system. Installation of virtual environment is recommended
3. Make sure the .csv file is placed in the same folder as the .py file.
4. Refer to .ipynb for detailed explaination of each step.