The Elements Of Statistical Learning

Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 9780387848587
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This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

Statistical Data Mining Using Sas Applications Second Edition

Author: George Fernandez
Publisher: CRC Press
ISBN: 1439810761
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Sarle, W. S., Ed., Neural Network FAQ, part 1 of 7: Introduction, periodic posting
to the Usenet newsgroup comp.ai.neural-nets, URL: ftp://ftp.sas.com/pub/neural/
FAQ.html (last accessed 3/10/10). 8. SAS Institute Inc., Neural Network Modeling
Course Notes, Cary, NC, 2000. 9. Hastie, T., Tibshirani, R., and Friedman, J., The
Elements of Statistical LearningData Mining, Inference, and Prediction,
Springer series in Statistics, New York, 2001, chap. 11. Johnson, R. A. and
Wichern, D. W., ...

Probability And Statistics With R Second Edition

Author: Maria Dolores Ugarte
Publisher: CRC Press
ISBN: 1466504404
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A Handbook of Small Data Sets. London: Chapman & Hall. Harrell, F. E., Jr. 2015
. Hmisc: Harrell Miscellaneous. http://CRAN.R-project.org/ package=Hmisc. R
package version 3.15-0. Hastie, T., R. Tibshirani, and J. Friedman. 2009. 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. Hennekens, C. 1988. Preliminary report: Findings from
the aspirin ...

Ensemble Machine Learning

Author: Cha Zhang
Publisher: Springer Science & Business Media
ISBN: 1441993258
Size: 50.49 MB
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22. 23. 24. 25. 26. Dettling, M.: BagBoosting for Tumor Classification with Gene
Expression Data. Bioinformatics 20 (18) pp. 3583–3593 (2004). 9. Diaz-Uriarte, R
., Alvarez de Andres, S.: Gene Selection and Classification of Microarray Data
Using Random Forest. BMC Bioinformatics 7 (1) 3 (2006). 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).

Data Mining Applications With R

Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 0124115209
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction,
second ed. Springer Series in Statistics, Springer, New York, NY, USA. Kohonen,
T., 1995. Self-Organizing Maps, Springer Series in Information Retrieval,
seconded. Springer, New York, NY, USA. Lang, D.T., Swayne, D., Wickham, H.,
Lawrence, M., 2011. RGGobi: interface between R and GGobi. R package
version 2.1.17. Lawrence, M., 2011. cairoDevice: cairo-based cross-platform
antialiased graphics ...

Advanced Techniques In Web Intelligence 1

Author: Juan D. Velásquez
Publisher: Springer
ISBN: 3642144616
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SIAM 2001 • Gerhard Weikum, Arnd Christian K ̈onig, Stefan Deßloch (Eds.):
Proceedings of the ACM SIGMOD International Conference on Management of
Data, Paris, France, June 13-18, 2004. ACM 2004 • 6th Atlantic ... The Elements
of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (
Springer Series in Statistics). Springer-Verlag, 2nd ed. 2009. • Inmon, W. H.
Building the Data Warehouse, 4rd Edition. Wiley Publishing, 2005. • Kimball, R.
and Ross, ...

Risk A Multidisciplinary Introduction

Author: Claudia Klüppelberg
Publisher: Springer
ISBN: 3319044869
Size: 49.74 MB
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High-throughput, high-quality genomic data in combination with efficient
statistical and computational tools are currently advancing our knowledge on the
inheritance of quantitative traits at mind boggling speed. These developments ...
In addition, the concepts for data mining to arrive at accurate predictions based
on high-dimensional data presented here are applicable to a plethora of
research fields and applications. ... Edition. Springer Series in Statistics (Springer
, Berlin, 2009) 4.

20th European Symposium Of Computer Aided Process Engineering

Author: S. Pierucci
Publisher: Elsevier
ISBN: 0444535705
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[8] Leo Breiman, Bagging Predictors. Machine Learning, 24:123-140, 1996. [9] B.
Efron, Estimating the error rate of a prediction rule: some improvements on
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1983. [10] Trevor Hastie, Robert Tibshirani, Jerome Friedman. The Elements of
Statistical Learning: Data Mining, Inference, and Prediction - Second Edition.
Springer Series in Statistics, 2009. [11] Ting Wang, Package random forests for
Matlab R13, ...

Introduction To High Dimensional Statistics

Author: Christophe Giraud
Publisher: CRC Press
ISBN: 1482237954
Size: 37.67 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. xviii, 643 p., 2013. I.A. Ibragimov, V.N. Sudakov, and B.S. Tsirel'son.
Norms of Gaussian sample functions, volume 550 of Lecture Notes in
Mathematics. Springer, 1976. Proceedings of the third Japan-USSR Symposium
on Probability Theory.

Monte Carlo Methods And Stochastic Processes

Author: Emmanuel Gobet
Publisher: CRC Press
ISBN: 149874625X
Size: 53.30 MB
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Res., 13(2):311–329, 1988. [72] F.H. Harlow and N. Metropolis. Computing and
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Winter/Spring:132–141, 1983. [73] T. Hastie, R. Tibshirani, and J. Friedman. The
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Series in Statistics. New York, NY: Springer, second edition, 2009. [74] W.K.
Hastings. MonteCarlo sampling methods using Markov chains and their
applications.