This algorithm works by assigning membership to each data point corresponding to each cluster center on the basis of the distance between the cluster center and the data point. The more the data is near to the cluster center more is its membership towards the particular […]
k-means is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters. The main idea is to define k centers, one for each […]