文章基本信息

标题：A Thorough Investigation on the Clustering and Classification Techniques in Various Applications
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作者：R. Malathi Ravindran ; Dr.N. Nalayini
期刊名称：Bonfring International Journal of Data Mining
印刷版ISSN：2250-107X
电子版ISSN：2277-5048
出版年度：2011
卷号：1
期号：Inaugural Special Issue
页码：18-21
DOI：10.9756/BIJDM.1004
语种：English
出版社：Bonfring
摘要：Data mining is the procedure of extorting patterns from data. At present, it is broadly used in various fields like profiling practices, such as marketing, observation, fraud detection and scientific discovery, bioinformatics research. In this survey, mainly give attention to the classification and clustering of data mining approaches. Data mining includes clustering with difficulties of very large datasets with several classes of different types. This inflicts individual computational need on significant clustering algorithms. Another thing is Classification which is a data mining related to machine learning approach used to identify group membership for data samples. The classification approaches like decision tree induction, Bayesian networks, k-nearest neighbor classifier, case-based reasoning, genetic algorithm and fuzzy logic techniques are used widely in many areas. The aim of this survey is to give a wide-ranging evaluation of different classification and clustering techniques in data mining. This investigation evidently analysis the clustering and classification in the review and finally concludes which is clustering and classification is better for various fields.
关键词：Data mining; Clustering; Classification; Knowledge Extraction; Support Vector Machine; K Means Clustering