期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2016
卷号：5
期号：3
页码：0577-0580
出版社：Shri Pannalal Research Institute of Technolgy
摘要：While increasing the data size the improvement in accuracy becomes better. This is true only up to a fixed size. After this point, the performance usually becomes stable. In the context of small data sets expecting better performance usually leads to failure. Data mining research community tries to address this problem case by case basis. In this paper we consider this study for diabetes and cancer datasets and establish the output showing the appropriate convergence of accuracy while increasing data size. This has been tested for different standard and familiar data mining tools. Comparative results are listed for the performance in classifying errors.
关键词：Weka; R package; KEEL; Knime; classifiers; ; Accuracy
