Assessing and Improving Prediction and Classification Theory and Alg
Carry out practical, real-life assessments of the performance of prediction and classification models written in C++. This book discusses techniques for improving the performance of such models by intelligent resampling of training/testing data, combining
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Assessing and Improving Prediction and Classification Theory and Algorithms in C++
Timothy Masters
Assessing and Improving Prediction and Classification: Theory and Algorithms in C++ Timothy Masters Ithaca, New York, USA ISBN-13 (pbk): 978-1-4842-3335-1 https://doi.org/10.1007/978-1-4842-3336-8
ISBN-13 (electronic): 978-1-4842-3336-8
Library of Congress Control Number: 2017962869
Copyright © 2018 by Timothy Masters This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Cover image by Freepik (www.freepik.com) Managing Director: Welmoed Spahr Editorial Director: Todd Green Acquisitions Editor: Steve Anglin Development Editor: Matthew Moodie Technical Reviewers: Massimo Nardone and Matt Wiley Coordinating Editor: Mark Powers Copy Editor: Kim Wimpsett Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail [email protected], or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail [email protected], or visit www.apress.com/ rights-permissions. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at www.apress.com/bulk-sales. Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the book’s product page, located at www.apress.com/9781484233351. For more detailed inf
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