Statistical Data Mining
INFT/CSI 979

Spring Semester 2003

• Bibliography (pdf)
• Instructions for Using CrystalVision (pdf)
• Course Lecture 1 (pdf)
• Course Lecture 2 (pdf)
• Course Lecture 3 (pdf)
• Course Lecture 4 (pdf)
• Course Lecture 5 (pdf)
• Course Lecture 5.5 (pdf)
• Course Lecture 6 (pdf)
  • Movie EM of fixed univariate data (mpeg)
  • Movie Adaptive mixtures for univariate data (mpeg)
  • Movie Adaptive mixtures for bivariate data (mpeg)
  • Movie Adaptive mixtures for trivariate data (mpeg)
• Course Lecture 7 (pdf)
• Course Lecture 8 (pdf)
• Course Lecture 9 (pdf)
• Course Lecture 10 (pdf)
• Course Lecture 11 (pdf)

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The lecture notes are Adobe pdf documents and require the Adobe Acrobat Reader version 4.0 or later, which may be obtained free from Adobe.

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• Notes on Project for Spring 2003
• Notes from 1996 Data Mining Course
• Crystal Vision Software
• Datasets are available from a number of sources
  • Dr. Wegman's Data Sets (zip, CrystalVision format)
  • Data and Software from StatLib at Carnegie Mellon University
  • Statistical Reference Datasets from NIST
• Some Data Mining Papers of Dr. Wegman
  • Visual Data Mining (pdf)
  • Data Compression by Geometric Quantization (pdf)
  • On Some Generalizations of Parallel Coordinates Plots (pdf)
  • On Some Mathematics for Visualizing High Dimensional Data (pdf)
  • Data Mining Strategies for the Detection of Chemical Warfare Agents (pdf)
  • On Some of Computer Graphics for Visualizing Densities (pdf)
  • Smoothing, Ridges, and Bumps (pdf)
  • Visualizing Cereal World (pdf)
  • Man vs. Machine - A Study of the Ability of Statistical Methodologies to Discern Human Generated ssh Traffic from Machine Generated scp Traffic (pdf)
  • Pixel Tours (pdf)
  • New Applications of the Image Grand Tour (pdf)
  • A Fast Algorithm for Approximating the Dominating Set of a Class Cover Catch Digraph (pdf)
  • A Text Stream Transformation for Semantic-Based Clustering (pdf)
  • Visual Clustering and Classification: The Oronsay Particle Size Data Set Revisted (html)
  • On Some Statistical Methods for Parallel Computation (pdf)
  • Modeling Continuous Time Series Driven by Fractional Gaussian Noise (pdf)
• Approved Project Topics:
  • Presentation (pdf)