KNN
KNN is a simple, supervised machine learning (ML) algorithm that can be used for classification or regression tasks – and is also frequently used in missing value imputation. It is based on the idea that the observations closest to a given data point are the most “similar” observations in a data set, and we can therefore classify unforeseen points based on the values of the closest existing points. By choosing K, the user can select the number of nearby observations to use in the algorithm.
Here, we will show you how to implement the KNN algorithm for classification, and show how different values of K affect the results. Continue reading Machine Learning – K-nearest neighbors (KNN)