The author has written an accessible book presenting the central issues and placing particular emphasis on comparison, performance assessment and how to match method to application. He reviews the different approaches and guides researchers (and the huge class of users and potential users) to suitable classes of techniques. He points the way to more detailed study in "further reading" sections in each chapter.
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Editorial Reviews
Review
"Evaluation rules are handled and the most important methods to calculate misclassification rates are presented." (Monatshefte fur Mathematik, Vol. 127, No. 2, 1999)
"...an accessible book..." (Zentralblatt Math, Vol. 997, No.22, 2002)
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The author has written an accessible book presenting the central issues and placing particular emphasis on comparison, performance assessment and how to match method to application. He reviews the different approaches and guides researchers (and the huge class of users and potential users) to suitable classes of techniques. He points the way to more detailed study in "further reading" sections in each chapter.
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Inside This Book
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First Sentence:
Researchers confronted with a classification problem for the first time sometimes ask, Which is the best type of classification rule? Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
design set objects, design set elements, constituent classifiers, regularised discriminant analysis, design set points, particular design set, classical linear discriminant analysis, covariance selection models, error rate estimators, optimal decision surface, nonparametric smoothing methods, positive predicted value, recursive partitioning methods, perceptron criterion, class conditional distributions, inaccuracy measure, neighbour methods, accurate probability estimates, resubstitution estimate, error rate estimation, pattern recognition community, offspring nodes, raw variables, nearest neighbour approach, apparent error rate New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Researchers confronted with a classification problem for the first time sometimes ask, Which is the best type of classification rule? Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
design set objects, design set elements, constituent classifiers, regularised discriminant analysis, design set points, particular design set, classical linear discriminant analysis, covariance selection models, error rate estimators, optimal decision surface, nonparametric smoothing methods, positive predicted value, recursive partitioning methods, perceptron criterion, class conditional distributions, inaccuracy measure, neighbour methods, accurate probability estimates, resubstitution estimate, error rate estimation, pattern recognition community, offspring nodes, raw variables, nearest neighbour approach, apparent error rate New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 100
books:
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100
books
cite this book:
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- Discrimination and Classification (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section) by David J. Hand in Front Matter, Back Matter (1), and Back Matter (2)
- Sample Survey Methods and Theory, Theory (Wiley Series in Probability and Statistics) (Volume 2) by Morris H. Hansen in Back Matter (1), and Back Matter (2)
- Convergence of Probability Measures (Wiley Series in Probability and Statistics) by Patrick Billingsley in Back Matter (1), and Back Matter (2)
- Multivariate Density Estimation: Theory, Practice, and Visualization (Wiley Series in Probability and Statistics) by David W. Scott in Back Matter
- Statistical Methods by John Delane Williams in Back Matter
See all 100 books this book cites
- Limit Theorems in Change-Point Analysis (Wiley Series in Probability & Statistics) by Miklós Csörgö in Back Matter (1), and Back Matter (2)
- Counterexamples in Probability, 2nd Edition by Jordan M. Stoyanov in Back Matter (1), and Back Matter (2)
- Data Mining and Knowledge Discovery with Evolutionary Algorithms by Alex A. Freitas on page 41, and page 136
- Statistical Shape Analysis by I. L. Dryden in Back Matter (1), and Back Matter (2)
- Credit Risk Modeling: Design and Application (Glenlake business monographs) by Elizabeth Mays on page 182, and page 190
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