Course contents:


Introduction to pattern recognition. Classification and clustering problems.

Generalization capability. Deduction and induction. Induction principle over normed spaces. Metric selection. Non-metric spaces. Point to point, point to cluster and cluster to cluster proximity measures. Mahalanobis distance.

Representation and pre-processing functions. Normalization. Missing Data. Ordinal and nominal discrete data. PCA.

Clustering algorithms: k-means and BSAS. Reinforcement Learning BSAS. The cluster validity problem; sensitivity index; relative validation indexes; Davies-Bouldin index, Silhouette index; clustering algorithms based on scale parameters; stability indexes; optimized clustering algorithms; constrained and unconstrained unsupervised modelling problems. Hierarchical clustering. Agent based clusters mining. Consensus. Introduction to fuzzy logic. Fuzzy clustering.

Classification systems: performance and sensitivity measures. Bayesian classifiers. Decision surfaces and discriminant functions characterization in the Gaussian case. Maximum likelihood estimation technique. Non-parametric estimation techniques. Classification model synthesis based on cluster analysis. Decision trees. Robust classification: voting techniques. Ensembles of classifiers.

Structured data taxonomy. Dissimilarity measures on structured data. Data fusion. Variable length domains: sequences of events, graphs. Bellman optimality principle; edit distance. Dissimilarity measures on labelled graph spaces (Graph Matching). Template matching techniques. Basic algorithms for image segmentation. Region descriptors: moments and geometric features.

Automatic Feature selection algorithms. Introduction to evolutionary optimization.

Granular Computing. Data Mining and Knowledge Discovery. Metric learning. Local metrics. Representations in dissimilarity spaces. Symbolic histograms.

Case studies and applications: signature recognition, text categorization and natural language processing, computer vision and image classification systems, mechanical diagnostics systems, pattern recognition in bioinformatics, trend prediction for financial time series.

Hardware acceleration on FPGAs and GPUs.