Giovanni seni (15 risultati)
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Da: HPB-Red, Dallas, TX, U.S.A.HPB-Red
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Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
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Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
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Da: HPB-Emerald, Dallas, TX, U.S.A.HPB-Emerald
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paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.
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Da: HPB-Diamond, Dallas, TX, U.S.A.HPB-Diamond
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EUR 12,52
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paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 50,13
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Ensemble Methods in Data Mining | Improving Accuracy Through Combining Predictions | Giovanni Seni (u. a.) | Taschenbuch | Synthesis Lectures on Data Mining and Knowledge Discovery | xvi | Englisch | 2010 | Springer | EAN 9783031007712 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tierg…artenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
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Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
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Condizione: New. Print on Demand This item is printed on demand.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 54,95
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PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: moluna, Greven, , Germaniamoluna
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EUR 28,42
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Giovanni Seni is a Senior Scientist with Elder Research, Inc. and directs ERI s Western office. As an active data mining practitioner in Silicon Valley, he has over 15 years R&D experience in statistical pattern reco…gnition, data mining, and human-computer .
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. They combine multiple models into one usually more accurate than the best of its components. Ensembles can provi…de a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability. Ensembles are useful with all modeling algorithms, but this book focuses on decision trees to explain them most clearly. After describing trees and their strengths and weaknesses, the authors provide an overview of regularization -- today understood to be a key reason for the superior performance of modern ensembling algorithms. The book continues with a clear description of two recent developments: Importance Sampling (IS) and Rule Ensembles (RE). IS reveals classic ensemble methods -- bagging, random forests, and boosting -- to be special cases of a single algorithm, thereby showing how to improve their accuracy and speed. REs are linear rule models derived from decision tree ensembles. They are the most interpretable version of ensembles, which is essential to applications such as credit scoring and fault diagnosis. Lastly, the authors explain the paradox of how ensembles achieve greater accuracy on new data despite their (apparently much greater) complexity.This book is aimed at novice and advanced analytic researchers and practitioners -- especially in Engineering, Statistics, and Computer Science. Those with little exposure to ensembles will learn why and how to employ this breakthrough method, and advanced practitioners will gain insight into building even more powerful models. Throughout, snippets of code in R are provided to illustrate the algorithms described and to encourage the reader to try the techniques.The authorsare industry experts in data mining and machine learning who are also adjunct professors and popular speakers. Although early pioneers in discovering and using ensembles, they here distill and clarify the recent groundbreaking work of leading academics (such as Jerome Friedman) to bring the benefits of ensembles to practitioners.Table of Contents: Ensembles Discovered / Predictive Learning and Decision Trees / Model Complexity, Model Selection and Regularization / Importance Sampling and the Classic Ensemble Methods / Rule Ensembles and Interpretation Statistics / Ensemble ComplexitySpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 156 pp. Englisch.
