The Elements Of Statistical Learning

Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 0387216065
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Data Mining, Inference, and Prediction Trevor Hastie, Robert Tibshirani, Jerome
Friedman. Springer. Series. in. Statistics. Andersen/Borgan/Gill/Keiding:
Statistical Models Based on Counting Processes. Atkinson/Riani: Robust ... Borg/
Groenen: Modern Multidimensional Scaling: Theory and Applications, 2nd
edition.

Statistical Inference For Ergodic Diffusion Processes

Author: Yury A. Kutoyants
Publisher: Springer Science & Business Media
ISBN: 144713866X
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Springer Series in Statistics Andersen/Borgan/Gill/Keiding: Statistical Models
Based on Counting Processes. ... Borg/Groenen: Modern Multidimensional
Scaling: Theory and Applications Brockwell/Davis: Time Series: Theory and
Methods, 2nd edition. ... Hastie/Tibshirani/Friedman: The Elements of Statistical
Learning: Data Mining, Inference, and Prediction Hedayat/Sloane/Stufken:
Orthogonal Arrays: ...

Statistical Data Mining Using Sas Applications Second Edition

Author: George Fernandez
Publisher: CRC Press
ISBN: 1439810761
Size: 46.90 MB
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The SAS data mining solution provides business technologists and quantitative
experts the necessary tools to obtain ... J., The Elements of Statistical Learning
Data Mining, Inference, and Prediction, Springer series in Statistics, New York, ...

Ensemble Machine Learning

Author: Cha Zhang
Publisher: Springer Science & Business Media
ISBN: 1441993258
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Diaz-Uriarte, R., Alvarez de Andres, S.: Gene Selection and Classification of
Microarray Data Using Random Forest. ... Hastie, T., Tibshirani, R., Friedman, J.:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction,
Second Edition. Springer Series in Statistics, Springer, New York (2009).
Goldstein, B.

Advanced Techniques In Web Intelligence 1

Author: Juan D. Velásquez
Publisher: Springer
ISBN: 3642144616
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Proceedings of the First SIAM International Conference on Data Mining, April 5-7,
2001, Chicaco, Illinois, USA. ... The Elements of Statistical Learning: Data Mining,
Inference, and Prediction, Second Edition (Springer Series in Statistics).

Data Mining Applications With R

Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 0124115209
Size: 21.10 MB
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Bayesian Data Analysis, Second Edition (Chapman & Hall/ CRC Texts in
Statistical Science), second ed. ... Springer Series in Statistics, Springer, New
York, NY, USA. Hastie, T., Tibshirani, R., Friedman, J., 2009. The Elements of
Statistical Learning: Data Mining, Inference, and Prediction, second ed. Springer
Series in ... Self-Organizing Maps, Springer Series in Information Retrieval,
seconded. Springer ...

Probability And Statistics With R Second Edition

Author: Maria Dolores Ugarte
Publisher: CRC Press
ISBN: 1466504404
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Statistical Procedures for Agricultural Research. ... The Elements of Statistical
Learning. Springer Series in Statistics. Springer, New York, second ed. http://dx.
doi.org/10. 1007/978-0-387-84858-7. Data mining, inference, and prediction.

20th European Symposium Of Computer Aided Process Engineering

Author: S. Pierucci
Publisher: Elsevier
ISBN: 0444535705
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We talked only about the attributes selection scheme; these selected attributes
can also be used for prediction with a neural network (e.g., a multilayer
perceptron). Random Forests ... The Elements of Statistical Learning: Data
Mining, Inference, and Prediction - Second Edition. Springer Series in Statistics,
2009. [11] Ting ...

Risk A Multidisciplinary Introduction

Author: Claudia Klüppelberg
Publisher: Springer
ISBN: 3319044869
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T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning: Data
Mining, Inference, and Prediction, Second Edition. Springer Series in Statistics (
Springer, Berlin, 2009) 4. C.R. Henderson, Applications of Linear Models in
Animal ...

Introduction To High Dimensional Statistics

Author: Christophe Giraud
Publisher: CRC Press
ISBN: 1482237954
Size: 57.45 MB
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The elements of statistical learning. Springer Series in Statistics. Springer, New
York, second edition, 2009. Data mining, inference, and prediction. R.A. Horn
and C.R. Johnson. Matrix analysis. 2nd ed. Cambridge: Cambridge University
Press.