Feature Selection for Knowledge Discovery and Data Mining

作者: Hiroshi Motoda , Huan Liu

DOI:

关键词: Feature selectionKnowledge extractionData scienceInformation retrievalData miningData pre-processingComputer scienceSoftware miningData stream miningProcess (engineering)ToolboxRaw data

摘要: From the Publisher: With advanced computer technologies and their omnipresent usage, data accumulates in a speed unmatchable by human's capacity to process data. To meet this growing challenge, research community of knowledge discovery from databases emerged. The key issue studied is, layman's terms, make advantageous use large stores In order raw useful, it is necessary represent, process, extract for various applications. Feature Selection Knowledge Discovery Data Mining offers an overview methods developed since 1970's provides general framework examine these categorize them. This book employs simple examples show essence representative feature selection compares them using sets with combinations intrinsic properties according objective selection. addition, suggests guidelines how different under circumstances points out new challenges exciting area research. intended be used researchers machine learning, mining, discovery, as toolbox relevant tools that help solving real-world problems. also serve reference or secondary text courses on databases.

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