GitHub - mohdasim8018/K-Means-using-Map-Reduce: Implemented K-Means algorithm using MapReduce to make it scalable. The inputs of the algorithm are the data file and the centroid file. The data file contains m data points. Each data point is represented as an n-dimensional numeric vector. The centroid file has K data points that are randomly chosen from the data file. The distance measure used here is Euclidian distance.

mohdasim8018 / K-Means-using-Map-Reduce Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

Implemented K-Means algorithm using MapReduce to make it scalable. The inputs of the algorithm are the data file and the centroid file. The data file contains m data points. Each data point is represented as an n-dimensional numeric vector. The centroid file has K data points that are randomly chosen from the data file. The distance measure used…