Tools

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010 a| 2022000819;

020 a| 9780367549800q| (hardcover);

020 a| 9780367549824q| (paperback);

020 z| 9781003091448q| (ebook);

035 a| (WaSeSS)ssj0002675822;

042 a| pcc;

049 a| EREEa| NEHH;

050 00 a| QA76.9.A955b| R38 2022;

082 00 a| 004.01/51132| 23/eng/20220416;

100 1 a| Rauch, Jan.=| ^A418413;

245 10 a| Mechanizing hypothesis formationh| [electronic resource] :b| principles and case studies /c| Jan Rauch, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia, Milan ¿¿im¿¿nek, Department of Systems Analysis, Prague University of Economics and Business, Prague, Czechia, David Chud©Łn, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia, Petr M©Ł¿Ła, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia;

250 a| First edition.;

260 a| Boca Raton :b| CRC Press ;b| Taylor and Francis Group,c| 2022.;

300 a| xiv, 345 pages ;c| 24 cm;

500 a| "CRC Press is an imprint of the Taylor & Francis Group, an Informa business.";

500 a| "A science publishers book.";

504 a| Includes bibliographical references (pages 322-338) and index.;

505 0 a| Data sets -- Principle and simple examples -- Common features -- LISp-Miner system -- Examples overview -- 4ft-Miner-GUHA association rules -- CF-Miner-histograms -- KL-Miner-pairs of categorical attributes -- SD4ft-Miner-couples of GUHA association rules -- SDCF-Miner-couples of histograms -- SDKL-Miner-couples of pairs of categorical attributes -- Miner-action rules -- GUHA procedures and business intelligence -- CleverMiner-GUHA and Python -- Artificial data generation and LM ReverseMiner module -- Applying domain knowledge -- Observational calculi.;

506 a| Available only to authorized users.;

520 a| "The GUHA is a method of mechanizing hypothesis formation. The input of the GUHA procedure consists of analysed data and several parameters defining a large set of relevant patterns. The output is a representation of a set of all relevant patterns satisfying the given true condition. Case studies concerning applications of GUHA procedures dealing with patterns in a form of enhanced association rules, couples of association rules, action rules, histograms, couples of histograms, and patterns based on general contingency tables are presented. Theoretical foundations based on observational calculi are introduced. An overview of the recent relevant research results is also available"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 0 a| Automatic hypothesis formation.=| ^A866609;

650 0 a| Data mining.=| ^A408868;

655 0 a| Electronic books.=| ^A491897;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003091448;

949 a| CLICK ON WEB ADDRESSw| ASISh| JOYNER188;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL77;

949 a| CLICK ON WEB ADDRESSw| ASISh| JMUSIC60;

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999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6675955-2001l| HSLELECm| HSLr| Ys| Yt| HEBKu| 12/19/2025x| EBOOKz| HERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6675955-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 12/19/2025x| EBOOKz| JERESOURCE;

Mechanizing hypothesis formation principles and case studies / Jan Rauch, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia, Milan ¿¿im¿¿nek, Department of Systems Analysis, Prague University of Economics and Business, Prague, Czechia, David Chud©Łn, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia, Petr M©Ł¿Ła, Department of Information and Knowledge Engineering Prague University of Economics and Business, Prague, Czechia.

Author/creator	Rauch, Jan
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton : CRC Press ; Taylor and Francis Group, 2022.
Description	xiv, 345 pages ; 24 cm
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Automatic hypothesis formation. Data mining.

Contents	Data sets -- Principle and simple examples -- Common features -- LISp-Miner system -- Examples overview -- 4ft-Miner-GUHA association rules -- CF-Miner-histograms -- KL-Miner-pairs of categorical attributes -- SD4ft-Miner-couples of GUHA association rules -- SDCF-Miner-couples of histograms -- SDKL-Miner-couples of pairs of categorical attributes -- Miner-action rules -- GUHA procedures and business intelligence -- CleverMiner-GUHA and Python -- Artificial data generation and LM ReverseMiner module -- Applying domain knowledge -- Observational calculi.
Abstract	"The GUHA is a method of mechanizing hypothesis formation. The input of the GUHA procedure consists of analysed data and several parameters defining a large set of relevant patterns. The output is a representation of a set of all relevant patterns satisfying the given true condition. Case studies concerning applications of GUHA procedures dealing with patterns in a form of enhanced association rules, couples of association rules, action rules, histograms, couples of histograms, and patterns based on general contingency tables are presented. Theoretical foundations based on observational calculi are introduced. An overview of the recent relevant research results is also available"-- Provided by publisher.
General note	"CRC Press is an imprint of the Taylor & Francis Group, an Informa business."
General note	"A science publishers book."
Bibliography note	Includes bibliographical references (pages 322-338) and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2022000819
ISBN	9780367549800 (hardcover)
ISBN	9780367549824 (paperback)
ISBN	(ebook)

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