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Statistical And Inductive Inference By Minimum Message Length (Hb)
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Statistical And Inductive Inference By Minimum Message Length (Hb)
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Statistical And Inductive Inference By Minimum Message Length (Hb)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length.
Publicado por Springer, 2005., 2005
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Añadir al carritoHardcover. Slight sunning to top edge of front cover and spine, otherwise very good condition. No dustjacket. Part of the Springer Information Science & Statistics series. 429pp. ISBN-10 038723795X ISBN-13: ISBN-13: 9780387237954.
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STATISTICAL AND INDUCTIVE INFERENCE BY MINIMUM MESSAGE LENGTH
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STATISTICAL AND INDUCTIVE INFERENCE BY MINIMUM MESSAGE LENGTH
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STATISTICAL AND INDUCTIVE INFERENCE BY MINIMUM MESSAGE LENGTH
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Edición internacionalSTATISTICAL AND INDUCTIVE INFERENCE BY MINIMUM MESSAGE LENGTH (HB)
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Statistical And Inductive Inference By Minimum Message Length
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical And Inductive Inference By Minimum Message Length
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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Statistical And Inductive Inference By Minimum Message Length
Libro 3 de 20: Information Science and StatisticsLibrería: GreatBookPricesUK, Woodford Green, Reino Unido
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsLibrería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Statistical and Inductive Inference by Minimum Message Length | C. S. Wallace | Taschenbuch | xvi | Englisch | 2010 | Humana | EAN 9781441920157 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Statistical And Inductive Inference By Minimum Message Length
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsLibrería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Mythanksareduetothemanypeoplewhohaveassistedintheworkreported here and in the preparation of this book. The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. MyworkleadingtothisbookbeganwhenDavidBoultonandIattempted to develop a method for intrinsic classi cation. Given data on a sample from some population, we aimed to discover whether the population should be considered to be a mixture of di erent types, classes or species of thing, and, if so, how many classes were present, what each class looked like, and which things in the sample belonged to which class. I saw the problem as one of Bayesian inference, but with prior probability densities replaced by discrete probabilities re ecting the precision to which the data would allow parameters to be estimated. Boulton, however, proposed that a classi cation of the sample was a way of brie y encoding the data: once each class was described and each thing assigned to a class, the data for a thing would be partially implied by the characteristics of its class, and hence require little further description. After some weeks' arguing our cases, we decided on the maths for each approach, and soon discovered they gave essentially the same results. Without Boulton's insight, we may never have made the connection between inference and brief encoding, which is the heart of this work.
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Statistical And Inductive Inference By Minimum Message Length
Libro 3 de 20: Information Science and StatisticsLibrería: GreatBookPricesUK, Woodford Green, Reino Unido
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EUR 179,38
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Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
Libro 3 de 20: Information Science and StatisticsLibrería: Mispah books, Redhill, SURRE, Reino Unido
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsPublicado por Springer-Verlag New York Inc., US, 2005
ISBN 10: 038723795X ISBN 13: 9780387237954
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Añadir al carritoHardback. Condición: New. 2005 ed. Mythanksareduetothemanypeoplewhohaveassistedintheworkreporte d here and in the preparation of this book. The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. MyworkleadingtothisbookbeganwhenDavidBoultonandIattempted to develop a method for intrinsic classi?cation. Given data on a sample from some population, we aimed to discover whether the population should be considered to be a mixture of di?erent types, classes or species of thing, and, if so, how many classes were present, what each class looked like, and which things in the sample belonged to which class. I saw the problem as one of Bayesian inference, but with prior probability densities replaced by discrete probabilities re?ecting the precision to which the data would allow parameters to be estimated. Boulton, however, proposed that a classi?cation of the sample was a way of brie?y encoding the data: once each class was described and each thing assigned to a class, the data for a thing would be partially implied by the characteristics of its class, and hence require little further description. After some weeks' arguing our cases, we decided on the maths for each approach, and soon discovered they gave essentially the same results. Without Boulton's insight, we may never have made the connection between inference and brief encoding, which is the heart of this work.
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsLibrería: moluna, Greven, Alemania
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Añadir al carritoGebunden. Condición: New. Since 1965, Professor Wallace and others have been developing an approach tostatistical estimation, hypothesis testing, model selection and their applications in the Artificial Intelligence field of Machine LearningMythanksareduetothemanypeoplewh.
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsPublicado por Springer-Verlag New York Inc., US, 2005
ISBN 10: 038723795X ISBN 13: 9780387237954
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
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Añadir al carritoHardback. Condición: New. 2005 ed. Mythanksareduetothemanypeoplewhohaveassistedintheworkreporte d here and in the preparation of this book. The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. MyworkleadingtothisbookbeganwhenDavidBoultonandIattempted to develop a method for intrinsic classi?cation. Given data on a sample from some population, we aimed to discover whether the population should be considered to be a mixture of di?erent types, classes or species of thing, and, if so, how many classes were present, what each class looked like, and which things in the sample belonged to which class. I saw the problem as one of Bayesian inference, but with prior probability densities replaced by discrete probabilities re?ecting the precision to which the data would allow parameters to be estimated. Boulton, however, proposed that a classi?cation of the sample was a way of brie?y encoding the data: once each class was described and each thing assigned to a class, the data for a thing would be partially implied by the characteristics of its class, and hence require little further description. After some weeks' arguing our cases, we decided on the maths for each approach, and soon discovered they gave essentially the same results. Without Boulton's insight, we may never have made the connection between inference and brief encoding, which is the heart of this work.
-
Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
Publicado por Springer, 2005
ISBN 10: 0071457453 ISBN 13: 9780071457453
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
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Añadir al carritoHardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Statistical and Inductive Inference By Minimum Message Length
Publicado por Springer, 2005
Librería: Books in my Basket, New Delhi, India
Calificación del vendedor: 5 de 5 estrellas
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Añadir al carritoHardcover. Condición: New. ISBN:9780387237954.
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Statistical and Inductive Inference by Minimum Message Length
Libro 3 de 20: Information Science and StatisticsPublicado por Springer New York Dez 2010, 2010
ISBN 10: 1441920153 ISBN 13: 9781441920157
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
EUR 117,69
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mythanksareduetothemanypeoplewhohaveassistedintheworkreported here and in the preparation of this book. The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. MyworkleadingtothisbookbeganwhenDavidBoultonandIattempted to develop a method for intrinsic classi cation. Given data on a sample from some population, we aimed to discover whether the population should be considered to be a mixture of di erent types, classes or species of thing, and, if so, how many classes were present, what each class looked like, and which things in the sample belonged to which class. I saw the problem as one of Bayesian inference, but with prior probability densities replaced by discrete probabilities re ecting the precision to which the data would allow parameters to be estimated. Boulton, however, proposed that a classi cation of the sample was a way of brie y encoding the data: once each class was described and each thing assigned to a class, the data for a thing would be partially implied by the characteristics of its class, and hence require little further description. After some weeks' arguing our cases, we decided on the maths for each approach, and soon discovered they gave essentially the same results. Without Boulton's insight, we may never have made the connection between inference and brief encoding, which is the heart of this work. 448 pp. Englisch.
