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Ensemble Classification Methods with Applications in R
An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Appl…
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A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense …
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Praise for the First Edition «. . . an excellent textbook . . . well organized and neatly written.» —Mathematical Reviews «. . . amazingly interesting…
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The definitive resource for survey questionnaire testing and evaluation Over the past two decades, methods for the development, evaluation, and testin…
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Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or method…
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Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years. New and emerging applicatio…
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A Complete Introduction to probability AND its computer Science Applications USING R Probability with R serves as a comprehensive and introductory boo…
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One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier …
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Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Reliability Data was…
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Multivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a s…
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Applies the well-developed tools of the theory of weak convergence of probability measures to large deviation analysis–a consistent new approach The t…
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Generalised Least Squares adopts a concise and mathematically rigorous approach. It will provide an up-to-date self-contained introduction to the unif…
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A systematic introduction to partial differential equations and modern finite element methods for their efficient numerical solution Partial Different…
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A resource for probability AND random processes, with hundreds of worked examples and probability and Fourier transform tables This survival guide in …
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Fundamental concepts of mathematical modeling Modeling is one of the most effective, commonly used tools in engineering and the applied sciences. In t…
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The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The applic…
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A comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, and scattered across many different journals. Weib…
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The first systematic, book-length treatment of the subject. Begins with a general introduction and the formal mathematical background behind qualitati…
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Scaling is a mathematical transformation that enlarges or diminishes objects. The technique is used in a variety of areas, including finance and image…
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A fascinating chronicle of the lives and achievements of the men and women who helped shapethe science of statistics This handsomely illustrated volum…
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Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regressi…
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An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences fr…
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