文章基本信息

标题：The Evaluation and Comparative Study with a New Clustered Based Machine Learning Algorithm
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作者：Alauddin Alomary ; Mohammad Jamil
期刊名称：The International Arab Journal of Information Technology
印刷版ISSN：1683-3198
出版年度：2006
卷号：3
期号：4
出版社：Zarqa Private University
摘要：In this paper, a clustering based machine learning algorithm called Clustering Algorithm System (CAS) is introduced. The CAS algorithm is tested to evaluate its performance and find fruitful results. We have been presented some heuristics to facilitate machine-learning authors to boost up their research works. The InfoBase of the Ministry of Civil Services is used to analyze the CAS algorithm. The CAS algorithm was compared with other machine learning algorithms like UNIMEM, COBWEB, and CLASSIT and was found to have some strong points over them. The proposed algorithm combined advantages of two different approaches to machine learning. The first approach is learning from examples, CAS supports single and multiple inheritance and exceptions. CAS also avoids probability assumptions which are well understood in concept formation. The second approach is learning by observation. CAS applies a set of operators that have proven to be effective in conceptual clustering. We have shown how CAS builds and searches through a clusters hierarchy to incorporate or characterize an object
关键词：Clustering algorithm; unsupervised learning; evidential reasoning; incremental learning; multiple inheritances; overlapping concept.