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Statistical Learning for Biomedical Data (Practical Guides to Biostatistics and Epidemiology) - Softcover
Synopsis
This highly motivating introduction to statistical learning machines explains underlying principles in nontechnical language, using many examples and figures.
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About the Authors
James D. Malley is a Research Mathematical Statistician in the Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, at the National Institutes of Health.
Karen G. Malley is president of Malley Research Programming, Inc. in Rockville, Maryland, providing statistical programming services to the pharmaceutical industry and the National Institutes of Health. She also serves on the global council of the Clinical Data Interchange Standards Consortium (CDISC) user network, and the steering committee of the Washington, DC area CDISC user network.
Sinisa Pajevic is a Staff Scientist in the Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, at the National Institutes of Health.
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Statistical learning for biomedical data
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