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Editore: Springer, 2016
ISBN 10: 331937723XISBN 13: 9783319377230
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Libro
Condizione: New.
Editore: Springer, 2013
ISBN 10: 3319009591ISBN 13: 9783319009599
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Libro
Condizione: New.
Editore: Springer International Publishing, 2013
ISBN 10: 3319009591ISBN 13: 9783319009599
Da: moluna, Greven, Germania
Libro Print on Demand
Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a general meta-learning approach which is applicable to a variety of machine learning algorithms Focuses on different variants of decision tree induction Details the long and complex road from various small and larger algorithms to.
Editore: Springer International Publishing, 2016
ISBN 10: 331937723XISBN 13: 9783319377230
Da: moluna, Greven, Germania
Libro Print on Demand
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a general meta-learning approach which is applicable to a variety of machine learning algorithms Focuses on different variants of decision tree induction Details the long and complex road from various small and larger algorithms to.
Editore: Springer-Verlag New York Inc, 2016
ISBN 10: 331937723XISBN 13: 9783319377230
Da: Revaluation Books, Exeter, Regno Unito
Libro
Paperback. Condizione: Brand New. reprint edition. 360 pages. 9.25x6.10x0.82 inches. In Stock.
Editore: Springer, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: booksXpress, Bayonne, NJ, U.S.A.
Libro
Hardcover. Condizione: new.
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: booksXpress, Bayonne, NJ, U.S.A.
Libro
Soft Cover. Condizione: new.
Editore: Springer Berlin Heidelberg Aug 2013, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Libro Print on Demand
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field. 372 pp. Englisch.
Editore: Springer Berlin Heidelberg, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: moluna, Greven, Germania
Libro Print on Demand
Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Meta-learning in computational intelligence Presents new Developments and Trends in Computational Intelligence and Learning Written by leading experts in the fieldComputational Intelligence (CI) community has de.
Editore: Springer Berlin Heidelberg, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: moluna, Greven, Germania
Libro Print on Demand
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Meta-learning in computational intelligence Presents new Developments and Trends in Computational Intelligence and Learning Written by leading experts in the fieldComputational Intelligence (CI) community has de.
Editore: Springer, 2013
ISBN 10: 3319009591ISBN 13: 9783319009599
Da: Mispah books, Redhill, SURRE, Regno Unito
Libro
Hardcover. Condizione: Like New. Like New. book.
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Libro
Condizione: New.
Editore: Springer, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Libro
Condizione: New.
Editore: Springer Berlin Heidelberg, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: AHA-BUCH GmbH, Einbeck, Germania
Libro
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Editore: Springer Berlin Heidelberg Jun 2011, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Libro Print on Demand
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field. 372 pp. Englisch.
Editore: Springer, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: Ria Christie Collections, Uxbridge, Regno Unito
Libro Print on Demand
Condizione: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: Ria Christie Collections, Uxbridge, Regno Unito
Libro Print on Demand
Condizione: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Editore: Springer Berlin Heidelberg, 2011
ISBN 10: 3642209793ISBN 13: 9783642209796
Da: AHA-BUCH GmbH, Einbeck, Germania
Libro
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: Books Puddle, New York, NY, U.S.A.
Libro
Condizione: New. pp. 372.
Editore: Springer, 2016
ISBN 10: 331937723XISBN 13: 9783319377230
Da: dsmbooks, Liverpool, Regno Unito
Libro
Paperback. Condizione: Like New. Like New. book.
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: Majestic Books, Hounslow, Regno Unito
Libro Print on Demand
Condizione: New. Print on Demand pp. 372 1237 Illus. (76 Col.).
Editore: Springer, 2013
ISBN 10: 3642268587ISBN 13: 9783642268588
Da: Revaluation Books, Exeter, Regno Unito
Libro
Paperback. Condizione: Brand New. 2011 edition. 372 pages. 9.25x6.10x0.88 inches. In Stock.