9781108494205 - model-based clustering and classification for data science: with applications in r di bouveyron, charles; celeux, gilles; murphy, t. brendan; raftery, adrian e. (26 risultati)
Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press CUP 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science : With Applications in R
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
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Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Model-Based Clustering and Classification for Data Science : With Applications in R
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
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Model-Based Clustering and Classification for Data Science : With Applications in R
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
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Model-Based Clustering and Classification for Data Science: With Applications in R: 50 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)
Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery
Lingua: Inglese
Editore: Cambridge University Press 2019-07-25 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Editore: Cambridge University Press 2019
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Condizione: New. 2019. Hardcover. . . . . .
Model-Based Clustering and Classification for Data Science : With Applications in R
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
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Model-Based Clustering and Classification for Data Science
T. Brendan Murphy, Adrian E. Raftery, Charles Bouveyron, Gilles Celeux
Lingua: Inglese
Editore: Cambridge University Press, GB 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Hardback. Condizione: New. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observation…s, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics)
Bouveyron, Charles, Celeux, Gilles, Murphy, T. Brendan, Raft
Lingua: Inglese
Editore: Cambridge University Press 2019
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Condizione: New. 2019. Hardcover. . . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: CAMBRIDGE 2019
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Gebunden. Condizione: New. This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction .
Model-based Clustering and Classification for Data Science: With Applications in R
Bouveyron, Charles/ Celeux, Gilles/ Murphy, T. Brendan/ Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge Univ Pr 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Hardcover. Condizione: Brand New. 427 pages. 10.00x7.00x1.00 inches. In Stock.
Lingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.
Model-Based Clustering and Classification for Data Science
T. Brendan Murphy, Adrian E. Raftery, Charles Bouveyron, Gilles Celeux
Lingua: Inglese
Editore: Cambridge University Press, GB 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Hardback. Condizione: New. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observation…s, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Hardcover. Condizione: new. Hardcover. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified… observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics. This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction methods, using extensive data examples and providing R code for many methods. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Model-based Clustering and Classification for Data Science: With Applications in R
Bouveyron, Charles/ Celeux, Gilles/ Murphy, T. Brendan/ Raftery, Adrian E.
Lingua: Inglese
Editore: Cambridge Univ Pr 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
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Hardcover. Condizione: Brand New. 427 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.
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Lingua: Inglese
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Hardcover. Condizione: new. Hardcover. Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified… observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics. This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction methods, using extensive data examples and providing R code for many methods. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Altre immaginiLingua: Inglese
Editore: Cambridge University Press 2019
Serie: Cambridge Series in Statistical and Probabilistic Mathematics, Libro 1 di 46. Libro 1 di 46 - Cambridge Series in Statistical and Probabilistic Mathematics
- Rilegato
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Buch. Condizione: Neu. Model-based Clustering and Classification for Data Science | Charles Bouveyron (u. a.) | Buch | Gebunden | Englisch | 2019 | Cambridge University Press | EAN 9781108494205 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on De…mand.
