Machine Learning in Medicine: Part Three
Author:   Ton J. Cleophas ,  Aeilko H. Zwinderman
Publisher:   Springer
Edition:   Softcover reprint of the original 1st ed. 2013
ISBN:  

9789402402605


Pages:   224
Publication Date:   30 April 2017
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Machine Learning in Medicine: Part Three


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Full Product Details

Author:   Ton J. Cleophas ,  Aeilko H. Zwinderman
Publisher:   Springer
Imprint:   Springer
Edition:   Softcover reprint of the original 1st ed. 2013
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   3.752kg
ISBN:  

9789402402605


ISBN 10:   9402402608
Pages:   224
Publication Date:   30 April 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Preface.- Introduction to Machine Learning Part Three.- Evolutionary Operations.- Multiple Treatments.- Multiple Endpoints.- Optimal Binning.- Exact P-Values.- Probit Regression.- Over - dispersion.10 Random Effects.- Weighted Least Squares.- Multiple Response Sets.- Complex Samples.- Runs Tests.- Decision Trees.- Spectral Plots.- Newton's Methods.- Stochastic Processes, Stationary Markov Chains.- Stochastic Processes, Absorbing Markov Chains.- Conjoint Models.- Machine Learning and Unsolved Questions.- Index.

Reviews

From the reviews: This book is excellent. It is valuable source of a basic understanding of novel machine learning methods of clinical data analysis and can be used as a reference by students and teachers of epidemiology, statistics and biostatistics, computer and social scientists, and clinical investigators. (Vedang J. Bhavsar, Doody's Book Reviews, March, 2014)


From the reviews: This book is excellent. It is valuable source of a basic understanding of novel machine learning methods of clinical data analysis and can be used as a reference by students and teachers of epidemiology, statistics and biostatistics, computer and social scientists, and clinical investigators. (Vedang J. Bhavsar, Doody's Book Reviews, March, 2014)


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