文章基本信息

标题：Empirical Evaluation of Classifiers’ Performance Using Data Mining Algorithm
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作者：Sanjay Kumar Sen ; Dr. Sujata Dash
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：21
期号：3
页码：146-155
DOI：10.14445/22312803/IJCTT-V21P128
出版社：Seventh Sense Research Group
摘要：The field of data mining and knowledge discovery in databases (KDD) has been growing in leaps and bounds, and has shown great potential for the future[10]. Data classification is an important task in KDD (knowledge discovery in databases) process. It has several potential applications. The performance of a classifier is strongly dependent on the learning algorithm. In this paper, we describe our experiment on data classification considering several classification models. We tabulate the experimental results and present a comparative analysis thereof.
关键词：Knowledge discovery in databases; classifier; data classification.