Abstract: In today’s world, gigantic amount of data is available in science, industry, business and many other areas. This data can provide valuable information which can be used by management for making important decisions. But problem is that how can find valuable information. The answer is data mining. The work focuses on the fundamental concept of the Data mining i.e. Clustering and Classification Techniques. Clustering is done by analyzing k-means algorithm and classification techniques such as J48 and NAÏVE BAYES. Cluster is a group of objects that belongs to the same class. In other words, similar objects are grouped in one cluster and dissimilar objects are grouped in another cluster. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters. Classification is an important data mining technique with broad applications. It classifies data of various kinds. Classification is used to classify each item in a set of data into one of predefined set of classes or groups. This work has been carried out to make a performance evaluation of Naïve Bayes and j48 classification algorithm. Naive Bayes algorithm is based on probability and j48 algorithm is based on decision tree, that to make comparative evaluation of classifiers J48 and NAÏVE BAYES.
Keywords: Classification, Clustering, J48, Naïve Bayes, k-means, unsupervised learning.
Title: Analysis of K-Means Algorithm Using Classification Techniques in Mammographic Dataset
Author: Mrs. K.K. Kavitha, Ms. S. Kiruthiga
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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