k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype
of the cluster.
Data Poinst--These can be added on mouse click on the canvas,randomly with the quantity specified.
Centrois--These can be added on mouse click on the canvas,randomly with the quantity specified.(max limit being 10)
Algorithm--Here on clicking the RUN buttont the algo runs and classifies the data points into of the classes and CENTROID-POSITIOM when clicked modifies the poisition of the centre.
Two-dimensional visualization of k-means clustering algorithm