[PDF.46im] The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)
Trevor Hastie, Robert Tibshirani, Jerome Friedman
[PDF.na51] The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)
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| #445241 in Books | 2003-07-30 | Original language:English | PDF # 1 | 9.75 x6.50 x1.25l,1.10 | File type: PDF | 552 pages||59 of 60 people found the following review helpful.| Actually does something (huge) with the math|By John Mount|I have been using The Elements of Statistical Learning for years, so it is finally time to try and review it.
The Elements of Statistical Learning is a comprehensive mathematical treatment of machine learning from a statistical perspective. This means you get good derivations of popular methods such as sup|||From the reviews: |SIAM REVIEW |"The book is very well written and color is used throughout. Color adds a dimension that can be used to help the reader visualize high-dimensional data, and it is also very useful to help the eye see patterns and clusters more
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with...
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