文章基本信息

标题：MANAP:Hybrid Clustering and Classification for Entropy Reduction: A Review
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作者：Palwinder kaur ; Usvir kaur ; Dr. Dheerendra Singh 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：5
出版社：S&S Publications
摘要：Clustering is the unsupervised learning problem. Better Clustering improves accuracy of search results andhelps to reduce the retrieval time. Clustering dispersion known as entropy which is the disorderness that occur afterretrieving search result. It can be reduced by combining clustering algorithm with the classifier. Clustering with weightedk-mean results in unlabelled data. Unlabelled data can be labelled by using neural network and support vector machines. Aneural network is an interconnected group of nodes, for classifying data whereas SVM is the classification function todistinguish between members of the two classes in the training data. For classification we use neural networks and SVM asthey can recognize the patterns.
关键词：Clustering; Weighted k-mean; Neural network classifier; SVM classifier; Entropy reduction system