期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2011
卷号：2
期号：4Ver 3
出版社：Ayushmaan Technologies
摘要：Data mining is the process of extracting hidden knowledge from the large data repositories. In data mining, there are several techniques and algorithms are used for extracting the hidden information and finding the relationships between them. Classification is one of the popular techniques of data mining. Classification is a data mining technique which is used to predict group membership for the instances of data. Classification is the task of generalizes the known structure to apply to new data. Classification involves finding rules that partition the data into disjoint groups. Many classification rule algorithms are used to generate the classification rules such as ID3, CART, and uRule. In this research work, we have analyzed the performance of the three classification rule algorithms, namely C4.5, RIPPER and PART algorithms.
