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Reverse Hypothesis Machine Learning : A Practitioner's Perspective / / by Parag Kulkarni



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Autore: Kulkarni Parag Visualizza persona
Titolo: Reverse Hypothesis Machine Learning : A Practitioner's Perspective / / by Parag Kulkarni Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Edizione: 1st ed. 2017.
Descrizione fisica: 1 online resource (XVI, 138 p. 61 illus., 9 illus. in color.)
Disciplina: 006.31
Soggetto topico: Computational intelligence
Knowledge management
Machinery
Management
Industrial management
Electronics
Microelectronics
Computational Intelligence
Knowledge Management
Machinery and Machine Elements
Innovation/Technology Management
Electronics and Microelectronics, Instrumentation
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Pattern Apart -- Understanding Machine Learning Opportunities -- Systemic Machine Learning -- Reinforcement and Deep Reinforcement Machine Learning -- Creative Machine Learning -- Co-operative and Collective learning for Creative Machine Learning -- Building Creative Machines with Optimal Machine Learning and Creative Machine Learning Applications -- Conclusion – Learning Continues.
Sommario/riassunto: This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts. It can also used by practitioners to develop new machine learning applications to solve problems that require creativity.
Titolo autorizzato: Reverse Hypothesis Machine Learning  Visualizza cluster
ISBN: 3-319-55312-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910254341403321
Lo trovi qui: Univ. Federico II
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Serie: Intelligent Systems Reference Library, . 1868-4394 ; ; 128