ΠΑΝΕΠΙΣΤΗΜΙΟ ΙΩΑΝΝΙΝΩΝ - ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ SITE MAP | uoi ΕΛΛΗΝΙΚΑ | uoi ENGLISH
Pattern Recognition

(Undergraduate Course)

 

COURSE_ID:
MYE002
WEEKLY HOURS:
3, 0, 2
SEMESTER:
-
COURSE UNITS:
4
ECTS CREDITS:
5.00
YEAR 2018/2019:
YES
PREREQUISITE:
-
DESCRIPTION:
Introductory concepts. Bayes Decision theory, Bayes error, the normal density, discriminant functions for the normal density. Non-parametric density estimation: Parzen-windows and k-nearest neighbors. Parametric density estimation: Unbiased estimator, likelihood function, maximum likelihood estimation, application on the general multivariate case, maximum a-posteriori estimation. Mixture models. Linear classifiers: linear functions and decision surfaces, perceptron algorithm. Nonlinear classifiers: multilayer feedforward neural networks, generalized linear classifiers (polynomial classifiers, radial basis function classifiers). Support vector machines. Kernel-based classifiers. Unsupervised learning: clustering, k-means algorithm, hierarchical clustering. Dimension Reduction: feature extraction and feature selection methods, principal component analysis (PCA) and Linear discriminant analysis (LDA).
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©2010 DEPARTMENT OF style="font-size: 0.1px;">COMPUTER SCIENCE style="font-size: 0.1px;">& ENGINEERING style="font-size: 0.1px;">UNIVERSITY style="font-size: 0.1px;">OF style="font-size: 0.1px;">IOANNINA