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Pattern Classification and Clustering - ia Tech probability and statistical basis for pattern classification and clustering, Bayesian classification decision theory, density and parameter estimation, dimensionality reduction, nonparametric estimation and classification, linear discriminant functions, feature extraction, parametric and
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EEL 6562 -- Image Processing and Computer Vision Course Description This is a 3-credit course The objective of this course is to impart a working knowledge of several important and widely used pattern recognition topics to the students through a mixture of motivational applications and theory
Chapter 3 Solutions | Pattern Classification 2nd Edition , (a) For scalar data fit to a Gaussian model, the maximum likelihood mean and variance are given by equations (16) and (17) Note that equation (16) is just the sample mean, while equation (17) is the (biased) sample variance
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Pattern Classification - Michigan State University Pattern Classification All materials in these slides were taken from Pattern Classification (2nd ed) by R O Duda, P E Hart and D G Stork, John Wiley
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