We can understand the working of K-Means clustering algorithm with the help of following steps −Step 1 − First, we need to specify the number of clusters, K, need to be generated by this algorithm. Step 2 − Next, randomly select K data points and assign each data point to a ...
K-means clustering is the most common partitioning algorithm. K-means reassigns each data in the dataset to only one of the new clusters formed. A record or data point is assigned to the nearest cluster using a measure of distance or similarity. The k-means algorithm creates the input parame...