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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)

Trevor Hastie, Robert Tibshirani, Jerome Friedman




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 | #508109 in Books |  2003-07-30 | Original language:English | PDF # 1 |  9.75 x6.50 x1.25l,1.10 | File type: PDF | 552 pages

||0 of 0 people found the following review helpful.| Good ELEMENTARY text book - not for advanced or research level use.|By MR Brain|This book is indeed elementary and only alludes to the actual theory of statistical learning. However, this book is useful as a very first step into the practical use of statistical learning.|0 of 0 people found the following review helpful.| Five Stars|By| ||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...

You easily download any file type for your device.The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics)   |  Trevor Hastie, Robert Tibshirani, Jerome Friedman. Which are the reasons I like to read books. Great story by a great author.

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