A Systematic Review on Educational Data Mining

In this paper, implementing K-Means clustering algorithm for analyzing the particular dataset and data mining. The main purpose is WEKA process. In Weka process we can get perfect graph, accuracy and random process. The Pre-processing was important concept it may clear a null values, removes a unwanted data and unwanted memory space. In Data mining analyzing data set. In Data mining implementing two methods classification, clustering process. By using classification, clustering we get flexible result and large amount of database. Here, weka process and K-means algorithm going to compare whether both graphs are accurate manner.