K Nearest Neighbors Regression

This module contains an implementation of K-Nearest Neighbors Regression, a simple yet effective algorithm for predicting continuous outcomes based on input features.

Usage

To use K-Nearest Neighbors Regression, follow these steps:

1. Import the KNNRegression class.
2. Create an instance of the class, specifying the number of neighbors (k).
3. Fit the model to your training data using the fit method.
4. Make predictions using the predict method.

Example:

from KNearestNeighborsRegression import KNNRegression

knn_model = KNNRegression(k=3)
knn_model.fit(X_train, y_train)
predictions = knn_model.predict(X_test)

Parameters

• k: Number of neighbors to consider for prediction.

Installation

To use this module, make sure you have the required dependencies installed:

pip install numpy

Coded By

Avdhesh Varshney

Happy Coding 👦