Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
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Statistical Learning for Biomedical Data (Hardcover, New title)
Loot Price: R3,478
Discovery Miles 34 780
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Statistical Learning for Biomedical Data (Hardcover, New title)
Series: Practical Guides to Biostatistics and Epidemiology
Expected to ship within 10 - 15 working days
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This book is for anyone who has biomedical data and needs to
identify variables that predict an outcome, for two-group outcomes
such as tumor/not-tumor, survival/death, or response from
treatment. Statistical learning machines are ideally suited to
these types of prediction problems, especially if the variables
being studied may not meet the assumptions of traditional
techniques. Learning machines come from the world of probability
and computer science but are not yet widely used in biomedical
research. This introduction brings learning machine techniques to
the biomedical world in an accessible way, explaining the
underlying principles in nontechnical language and using extensive
examples and figures. The authors connect these new methods to
familiar techniques by showing how to use the learning machine
models to generate smaller, more easily interpretable traditional
models. Coverage includes single decision trees, multiple-tree
techniques such as Random Forests (TM), neural nets, support vector
machines, nearest neighbors and boosting.
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