Analysis of Electricity Consumption at Home Using K-means Clustering Algorithm

Machine learning is a modern field that has emerged as a new tool for data analytics in the distributed computing environment. There are several aspects, at which, machine learning has improved the processing capacity along with effectiveness of analysis. In this paper, the electricity usage of home is analyzed through K-means clustering algorithm for obtaining the optimal home usage electricity data points. The Davis Boulden Index and Silhouette_score finds the detailed optimal number of clusters in the K-means algorithm and present the application scenario of the machine learning clustering analytics.