Genetic Programming Theory and Practice IX (Genetic and Evolutionary Computation)
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The Elements of Statistical Learning 2nd (second) edition Text Only
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics) 2nd ed. 2009. Corr. 3rd printing 5th Printing. edition
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
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Generalized Additive Models (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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Statistical Analysis of Gene Expression Microarray Data
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Generalized Additive Models: An Introduction with R (Chapman & Hall/CRC Texts in Statistical Science)
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Statistical Learning from a Regression Perspective (Springer Series in Statistics)
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Data Mining and Statistics for Decision Making (Wiley Series in Computational Statistics)
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Nonparametric Regression and Generalized Linear Models: A roughness penalty approach (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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Semiparametric Regression (Cambridge Series in Statistical and Probabilistic Mathematics)
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Pattern Recognition and Neural Networks
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Modern Regression Techniques Using R: A Practical Guide
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Statistical Models in S
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Local Polynomial Modelling and Its Applications: Monographs on Statistics and Applied Probability 66 (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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Exploratory Data Analysis with MATLAB (Chapman & Hall/CRC Computer Science & Data Analysis)
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Semiparametric Regression for the Social Sciences
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The Elements of Statistical Learning
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Cabinet 24: Shadows
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Local Regression and Likelihood (Statistics and Computing)
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A Statistical Approach to Neural Networks for Pattern Recognition (Wiley Series in Computational Statistics)
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Statistical Models in S (Wadsworth & Brooks/Cole Computer Science)
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The Elements of Statistical Learning Publisher: Springer; 2nd ed. 2009. Corr. 3rd printing 5th Printing. edition
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Multiple Classifier Systems: Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002. Proceedings (Lecture Notes in Computer Science)
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Bayesian backfitting (Technical report / Stanford University. Division of Biostatistics)
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Principal curves and surfaces
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Generalized Additive Models / The Axioms of Subjective Probability (Statistical Science: A Review of the Institute of Mathematical Statistics - August 1986, Vol. 1, No. 3)
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Statistical Models in S
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