This repository contains a KNN model that can be used to classify or regress data. The model is implemented in R. The KNN algorithm is a non-parametric, lazy learning algorithm for supervised learning. It works by finding the k most similar instances in the training set to a new instance, and then predicting the label of the new instance based on the labels of the k nearest neighbors.
The k value is a hyperparameter that must be chosen by the user. The value of k can affect the accuracy of the model, with higher values of k generally leading to more accurate predictions. However, higher values of k can also lead to less accurate predictions, as the model may be more likely to be influenced by outliers.
The KNN algorithm is a simple algorithm to implement, but it can be very effective for a variety of classification and regression tasks. It is often used as a benchmark algorithm for other machine learning algorithms.
