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Název:
Introduction to Feature Selection Toolbox 3 – The C++ Library for Subset Search, Data Modeling and Classification
Autoři: Somol, Petr ; Vácha, Pavel ; Mikeš, Stanislav ; Hora, Jan ; Pudil, Pavel ; Žid, Pavel
Typ dokumentu: Výzkumné zprávy
Rok: 2010
Jazyk: eng
Edice: Research Report, svazek: 2287
Abstrakt: We introduce a new standalone widely applicable software library for feature selection (also known as attribute or variable selection), capable of reducing problem dimensionality to maximize the accuracy of data models, performance of automatic decision rules as well as to reduce data acquisition cost. The library can be exploited by users in research as well as in industry. Less experienced users can experiment with different provided methods and their application to real-life problems, experts can implement their own criteria or search schemes taking advantage of the toolbox framework. In this paper we first provide a concise survey of a variety of existing feature selection approaches. Then we focus on a selected group of methods of good general performance as well as on tools surpassing the limits of existing libraries. We build a feature selection framework around them and design an object-based generic software library. We describe the key design points and properties of the library.
Klíčová slova: attribute selection; classification; feature selection; machine learning; optimization; pattern recognition; software library; subset search; variable selection
Číslo projektu: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), 2C06019 (CEP)
Poskytovatel projektu: GA MŠk, GA MŠk
Instituce: Ústav teorie informace a automatizace AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: http://fst.utia.cz/download/FST3_Introduction_UTIA_TR2287.pdf
Původní záznam: http://hdl.handle.net/11104/0195589
Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-42601
Záznam je zařazen do těchto sbírek:
Věda a výzkum > AV ČR > Ústav teorie informace a automatizace
Zprávy > Výzkumné zprávy
Autoři: Somol, Petr ; Vácha, Pavel ; Mikeš, Stanislav ; Hora, Jan ; Pudil, Pavel ; Žid, Pavel
Typ dokumentu: Výzkumné zprávy
Rok: 2010
Jazyk: eng
Edice: Research Report, svazek: 2287
Abstrakt: We introduce a new standalone widely applicable software library for feature selection (also known as attribute or variable selection), capable of reducing problem dimensionality to maximize the accuracy of data models, performance of automatic decision rules as well as to reduce data acquisition cost. The library can be exploited by users in research as well as in industry. Less experienced users can experiment with different provided methods and their application to real-life problems, experts can implement their own criteria or search schemes taking advantage of the toolbox framework. In this paper we first provide a concise survey of a variety of existing feature selection approaches. Then we focus on a selected group of methods of good general performance as well as on tools surpassing the limits of existing libraries. We build a feature selection framework around them and design an object-based generic software library. We describe the key design points and properties of the library.
Klíčová slova: attribute selection; classification; feature selection; machine learning; optimization; pattern recognition; software library; subset search; variable selection
Číslo projektu: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), 2C06019 (CEP)
Poskytovatel projektu: GA MŠk, GA MŠk
Instituce: Ústav teorie informace a automatizace AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: http://fst.utia.cz/download/FST3_Introduction_UTIA_TR2287.pdf
Původní záznam: http://hdl.handle.net/11104/0195589
Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-42601
Záznam je zařazen do těchto sbírek:
Věda a výzkum > AV ČR > Ústav teorie informace a automatizace
Zprávy > Výzkumné zprávy
Záznam vytvořen dne 2011-07-04, naposledy upraven 2024-01-26.