TY  - GEN
AU  - Arnold,Taylor
AU  - Kane,Michael
AU  - Lewis,Bryan W
TI  - A computational approach to statistical learning
T2  - Texts in Statistical Science
SN  - 9780367494049
U1  - 006.31015195 23
PY  - 2019///
CY  - Boca Raton
PB  - CRC Press
KW  - Statistical Science
KW  - Statistical Learning
KW  - Data Science
KW  - Machine Learning
N1  - Includes bibliographical references and index; 1. Introduction -- 2. Linear Models -- 3. Ridge Regression and principal component analysis -- 4. Linear Smoothers -- 5. Generalized linear models -- 6. Additive models -- 7. Penalized regression models -- 8. Neural networks -- 9. Dimensionality reduction -- 10. Computation in practice -- A Linear algebra and matrices -- B Floating point arithmetic and numerical computation
N2  - A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset
ER  -