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Seller: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, United Kingdom
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Add to basketCondition: Very Good. A lot of light scratches and minor shelf wear on cover. Also a light bend and crease on bottom corner of cover and pages throughout. Content is fine.
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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Hardcover/Pappeinband. Condition: Sehr gut. 330 p. Very good. Shrink wrapped. / Sehr guter Zustand. In Folie verschweißt. Sprache: Englisch Gewicht in Gramm: 798.
Condition: New. Well packaged and promptly shipped from California. Partnered with Friends of the Library since 2010.
Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639307674 ISBN 13: 9783639307672
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Evolutionary Applications for Financial Prediction | Classification Methods to Gather Patterns Using Genetic Programming | Alma Lilia Garcia Almanza (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639307672 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Add to basketCondition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639307674 ISBN 13: 9783639307672
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Add to basketPaperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Add to basketPaperback. Condition: Like New. Like New. book.
Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639307674 ISBN 13: 9783639307672
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents three applications, based on Machine Learning and Genetic Programming, which are devoted to find useful patterns to predict future events. The objective is to train the algorithms by using past data to produce a classifier that identifies the positive cases and discriminates the false alarms. This work uses examples for predicting future opportunities in financial stock markets in cases where the number of profitable opportunities is scarce. However, when the number of positive examples is small in comparison with the number of total cases, the identification of useful patterns becomes a serious challenge. Nevertheless, the objective of many real world problems, is precisely to identify the minority class as the fraud detection problem, or medical diagnosis and many other examples. The techniques of this book are suitable to deal with imbalanced data sets, provide comprehensible results that allow users to understand the factors that are involved in the decision, as well as to generate a range of solutions that let the user choose the best trade off according to their risk preferences.