
Department of
Computational
Perception


Special Topics: Exploratory Data Analysis
344.044, KV, 2h (3.0 ECTS), WS 2013/14
Assist.Prof. Dr.
Markus Schedl
Time: Tuesday,
13:4515:15
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 nonlinear
techniques for highdimensional
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),
Multidimensional Scaling (MDS), Sammon's Mapping, various fitness
functions
 SelfOrganizing Maps: SOM, GHSOM, Aligned SOM
 Visualizing SOMs: SOM grid, Music Description Map
(MDM), Bar Plots, Chernoff's Faces, UMatrix, Distance Matrix, Smoothed
Data Histogram (SDH), Component Planes
 Graphbased Methods: Locally Linear Embedding (LLE), Isomap,
Laplacian Eigenmaps
 Probabilistic Models: Generative Topographic Mapping (GTM),
Hierarchical GTM, tDistributed Stochastic Neighbor Embediing (tSNE)
 Random Projections, Locality Sensitive Hashing (LSH)
 Information Visualization: TreeMaps, InterRing/Sunburst,
Hyperbolic Browser, TimeSeries 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:
SelfOrganizing Maps (SOM): Basics, Online
and Batchlearning, hierarchical clustering, AlignedSOM
 Nov 26:
Visualization of SOMs: SOMgrid, MDM, Component Planes, UMatrix,
Distance Matrix, SDH, Bar Plots, Chernoff's Faces
 Dec 10:
Graphbased Methods: LLE, Isomap, Laplacian
Eigenmaps

Jan 07: Probabilistic Methods: GTM, Hierarchical
GTM, tDistributed 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