Department of Computational Perception

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Special Topics: Exploratory Data Analysis

344.044, KV, 2h (3.0 ECTS), WS 2013/14

Assist.-Prof. Dr. Markus Schedl

Time: Tuesday, 13:45-15:15
Start: Tuesday, Oct. 8, 2013
Location: S2 Z74

This class will be taught in English.

Class Objectives

This lecture gives an introduction to techniques, tools, and applications used in Visual Data Mining and methods underlying Exploratory Data Analysis. Special emphasis is given to linear and non-linear techniques for high-dimensional data projection, clustering (unsupervised learning), and related information visualization methods. Students will also be given the opportunity to implement and test these techniques in a pratical exercise.

The main topics covered will likely include:

Spectral Methods: Principal Components Analysis (PCA), Multi-dimensional Scaling (MDS), Sammon's Mapping, various fitness functions
Self-Organizing Maps: SOM, GHSOM, Aligned SOM
Visualizing SOMs: SOM grid, Music Description Map (MDM), Bar Plots, Chernoff's Faces, U-Matrix, Distance Matrix, Smoothed Data Histogram (SDH), Component Planes
Graph-based Methods: Locally Linear Embedding (LLE), Isomap, Laplacian Eigenmaps
Probabilistic Models: Generative Topographic Mapping (GTM), Hierarchical GTM, t-Distributed Stochastic Neighbor Embediing (tSNE)
Random Projections, Locality Sensitive Hashing (LSH)
Information Visualization: TreeMaps, InterRing/Sunburst, Hyperbolic Browser, Time-Series Visualization

Schedule

Oct 08: Introduction to Exploratory Data Analysis and Visual Data Mining
Oct 15: Principles and General Foundation of EDA and Data Projection Techniques, Similarity Measurement
Oct 29: Spectral Methods: PCA, MDS, Sammon's Mapping
Nov 19: Self-Organizing Maps (SOM): Basics, Online- and Batch-learning, hierarchical clustering, Aligned-SOM
Nov 26: Visualization of SOMs: SOM-grid, MDM, Component Planes, U-Matrix, Distance Matrix, SDH, Bar Plots, Chernoff's Faces
Dec 10: Graph-based Methods: LLE, Isomap, Laplacian Eigenmaps
Jan 07: Probabilistic Methods: GTM, Hierarchical GTM, t-Distributed Stochastic Neighbor Embediing (tSNE)
Jan 14: Information Visualization
Jan 21: Student's Presentations of Practical Exercise
Feb 28: Written Examination

last edited by pk on Sep 1, 2013