Optimal Feature Selection for Data Classification and Clustering: Techniques and Guidelines

International Journal of Information, Security and Systems Management

مقاله 5، دوره 5، شماره 2، شهریور 2016، صفحه 583-590   

نوع مقاله: Others

نویسندگان

Farhad Rad؛ Ali Asghar Nadri؛ Hamid Parvin

yasooj branch, islamic azad university

چکیده

In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intelligent feature selection system, involving crucial, decisive and effective factors in feature selection process. The procedure increases accuracy in classification and goodness of clusters. Finally, some of the problems and challenges facing the current and future feature selection processing are also discussed.

کلیدواژه‌ها

Feature selection؛ Classification؛ Clustering؛ categorizing framework؛ Evaluation Criteria