Download Some Books for Stat 602

Some Books for Stat 602
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning,
by Alan J. Izenman, (2008), ISBN-10: 0387781889, ISBN-13: 978-0387781884, Springer.
Principles and Theory for Data Mining and Machine Learning, by Bertrand Clarke, Ernest
Fokoué, and Hao Helen Zhang, (2009), ISBN-10: 0387981349, ISBN-13: 978-0387981345,
Springer.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition,
by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, (2009), ISBN-10: 0387848576,
ISBN-13: 978-0387848570, Springer.
An Introduction to Statistical Learning, by Gareth James, Daniela Witten, Trevor Hastie, and
Robert Tibshirani, (2013) ISBN-10: 1461471370, ISBN-13: 978-1461471370, Springer.
Applied Predictive Modeling, by Max Kuhn and Kjell Johnson, (2013), ISBN-10: 1461468485,
ISBN-13: 978-1461468486, Springer.
Spline Models for Observational Data (CBMS-NSF Regional Conference Series in Applied
Mathematics), by Grace Wahba, (1990), ISBN-10: 0898712440, ISBN-13: 978-0898712445,
SIAM.
Pattern Recognition and Machine Learning, by Christopher M. Bishop, (2006), ISBN-10:
0387310738, ISBN-13: 978-0387310732, Springer.
Machine Learning: A Probabilistic Perspective, by Kevin P. Murphy, (2012), ISBN-978-0-26201802-9, MIT Press.
Introduction to High-Dimensional Statistics, by Chritophe Giraud, (2105), ISBN-10:
1482237946, ISBN-13: 978-1482237948, CRC Press.
Foundations of Machine Learning, by Mehryar Mohri, Afshin Rostamizadeh, and Ameet
Talwalkar, (2012), ISBN-978-0-262-01825-8, MIT Press.
Learning From Data: A Short Course, by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and
Hsuan-Tien Lin, (2012), ISBN-10:600949-006-9, ISBN-13:978-1-60049-006-4, AMLbook.com.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, by Ian Witten,
Eibe Frank, and Mark Hall, (2011), ISBN978-0-12-374856-0 (pbk.), Morgan Kaufmann.
The following is about classification only:
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A Probabilistic Theory of Pattern Recognition, by Luc Devroye, László Györfi, and Gábor
Lugosi, (2013 reprint of 1996 edition), ISBN-10: 146126877X, ISBN-13: 978-1461268772 (soft
cover), Springer.
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