 Pattern Classification: A Unified View of Statistical and Neural Approaches
ISBN: 978-0-471-13534-0
Hardcover
392 pages
March 1996
US $139.95
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Statistical Decision Theory.
Need for Approximations: Fundamental Approaches.
Classification Based on Statistical Models Determined by First-and-Second Order Statistical Moments.
Classification Based on Mean-Square Functional Approximations.
Polynomial Regression.
Multilayer Perceptron Regression.
Radial Basis Functions.
Measurements, Features, and Feature Section.
Reject Criteria and Classifier Performance.
Combining Classifiers.
Conclusion.
STATMOD Program: Description of ftp Package.
References.
Index.
Need for Approximations: Fundamental Approaches.
Classification Based on Statistical Models Determined by First-and-Second Order Statistical Moments.
Classification Based on Mean-Square Functional Approximations.
Polynomial Regression.
Multilayer Perceptron Regression.
Radial Basis Functions.
Measurements, Features, and Feature Section.
Reject Criteria and Classifier Performance.
Combining Classifiers.
Conclusion.
STATMOD Program: Description of ftp Package.
References.
Index.
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