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Titlebook: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications; Muhammad Summair Raza,Usman Qamar Book 2

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書(shū)目名稱(chēng)Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
編輯Muhammad Summair Raza,Usman Qamar
視頻videohttp://file.papertrans.cn/942/941766/941766.mp4
概述Complete introduction of FS and RST (including background and practical applications).In-depth analysis of state-of-the-art tools and techniques (including strong and weak points and complexity analys
圖書(shū)封面Titlebook: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications; Muhammad Summair Raza,Usman Qamar Book 2
描述.The book will provide:..1) In depth explanation of rough set theory along with examples of the concepts...2) Detailed discussion on idea of feature selection..3) Details of various representative and state of the art feature selection techniques along with algorithmic explanations...4) Critical review of state of the art rough set based feature selection methods covering strength and weaknesses of each...5) In depth investigation of various application areas using rough set based feature selection...6) Complete Library of Rough Set APIs along with complexity analysis and detailed manual of using APIs..7) Program files of various representative Feature Selection algorithms along with explanation of each..The book will be a complete and self-sufficient source both for primary and secondary audience. Starting from basic concepts to state-of-the art implementation, it will be a constant source of help both for practitioners and researchers. .Book will provide in-depth explanation of concepts supplemented with working examples to help in practical implementation. As far as practical implementation is concerned, the researcher/practitioner can fully concentrate on his/her own work witho
出版日期Book 20171st edition
關(guān)鍵詞Feature Selection (FS); Rough Set Theory (RST); Attribute Reduction; Dimensionality Reduction; RSAR
版次1
doihttps://doi.org/10.1007/978-981-10-4965-1
isbn_softcover978-981-13-5278-2
isbn_ebook978-981-10-4965-1
copyrightThe Editor(s) (if applicable) and The Author(s) 2017
The information of publication is updating

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發(fā)表于 2025-3-21 22:29:11 | 只看該作者
Rough Set Theory, real-world data. Furthermore, it provides various methods to help analyse this data. This chapter discusses the basic concepts of RST with example to set a strong foundation of RST to be used as feature selection.
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Unsupervised Feature Selection Using RST,wever, in real world not all the data is properly labelled, so we may come across the situation where little or no class information is provided. For such type of data, we need unsupervised feature selection information that could find feature subsets without given any class labels. In this section,
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RST Source Code, libraries as well. The major aspect here is that the source code is also provided with each and every line explained. The explanation in this way will help research community to not only easily use the code but also they can modify as per their own research requirements. We have used Microsoft Exce
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