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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Muhammad Summair Raza; Usman Qamar

Springer Verlag, Singapore
2018
nidottu
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 without any concern towards implementation of basic RST functionality. Providing complexity analysis along with full working programs will further simplify analysis and comparison of algorithms.
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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Muhammad Summair Raza; Usman Qamar

Springer Verlag, Singapore
2019
sidottu
This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Muhammad Summair Raza; Usman Qamar

Springer Verlag, Singapore
2020
nidottu
This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
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Klinisch-pathologischer und DNA-Methylierungsstatus von Darmkrebs in Bangladesch

Klinisch-pathologischer und DNA-Methylierungsstatus von Darmkrebs in Bangladesch

Abu Khalid Muhammad Maruf Raza

Verlag Unser Wissen
2025
pokkari
Darmkrebs (CRC) ist die dritth ufigste Krebserkrankung weltweit und die zweith ufigste krebsbedingte Todesursache in den Vereinigten Staaten. Weltweit variiert die H ufigkeit von CRC stark. Das Lebenszeitrisiko, an CRC zu erkranken, liegt bei etwa 6 % oder einem von 18 Menschen. CRC ist auf dem indischen Subkontinent relativ selten. Die Inzidenz von Darmkrebs in Bangladesch ist nicht genau bekannt, scheint jedoch h ufig vorzukommen und tritt in j ngeren Altersgruppen mit einer leichten bergewichtigkeit bei M nnern auf. Das Durchschnittsalter bei der Diagnose liegt 10 Jahre unter dem in den Industriel ndern. Epigenetische Ver nderungen, also vererbbare Ver nderungen der Genfunktion, die nicht auf Ver nderungen der DNA-Sequenz zur ckzuf hren sind, sind ein wichtiger Mechanismus bei der Entstehung von Darmkrebs. DNA-Methylierungsanomalien sind wichtige epigenetische Ver nderungen bei Darmkrebs und stehen im Fokus der Krebsforschung. Bei Darmkrebs treten sowohl Hypermethylierungs- als auch Hypomethylierungsanomalien an verschiedenen genetischen Loci auf. Die Korrelation von histopathologischen Merkmalen mit klinischen Daten und die Erkennung von DNA-Methylierungsanomalien k nnen zu besseren Erkenntnissen in diesem Bereich beitragen.
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