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How Fuzzy Concepts Contribute to Machine Learning: 416 (Studies in Fuzziness and Soft Computing) - Hardcover
Inhaltsangabe
This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists.
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Über die Autorin bzw. den Autor
Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
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This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists.
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How Fuzzy Concepts Contribute to Machine Learning.
Verlag:
Cham, Springer International Publishing., 2022
ISBN 10: 3030940659
ISBN 13: 9783030940652
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Hardcover
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Anbieter: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Deutschland
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1st ed. 2022. XII, 167 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Fuzziness and Soft Computing, 416. Sprache: Englisch. Artikel-Nr. 13245DB
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How Fuzzy Concepts Contribute to Machine Learning
ISBN 10: 3030940659
ISBN 13: 9783030940652
Neu
Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Neuware -This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 180 pp. Englisch. Artikel-Nr. 9783030940652
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How Fuzzy Concepts Contribute to Machine Learning
Verlag:
Springer International Publishing, 2022
ISBN 10: 3030940659
ISBN 13: 9783030940652
Neu
Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces somecontemporaryapproacheson the application offuzzy and hesitant fuzzy sets in machine learning tasks such asclassification, clustering and dimensionreduction.Manysituationsarisein machine learning algorithmsinwhichapplying methods for uncertaintymodeling andmulti-criteriadecision making can lead toabetterunderstanding ofalgorithms behavior as well as achievinggood performances.Specifically,the present book is a collection of novel viewpointson howfuzzy andhesitant fuzzy conceptscan beappliedtodata uncertainty modeling aswell asbeing used to solvemulti-criteria decisionmaking challengesraised in machine learning problems. Using the multi-criteria decisionmaking framework, the book shows how different algorithms, rather thanhuman experts,areemployedto determine membership degrees. The book is expected to bring closerthe communities of pure mathematicians of fuzzysets and data scientists. Artikel-Nr. 9783030940652
Anzahl: 1 verfügbar