Visualization Methods for the Exploration of High Dimensional Data.

Abstract

This project focused on the development of data analysis and statistical methodology which may be characterized by one or more of the properties that they are large in size, high in dimension, and nonhomogeneous. The major thrust is in visualization on of both point clouds and mathematical structures in high dimensions. The specific advances made under this project are three dimensional generalizations of the Andrews plot, the grand tour in k-dimensions, fast algorithms for the pseudo-Grand Tour and structural inference using ridge estimation. (AN)

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Document Details

Document Type
Technical Report
Publication Date
Feb 16, 1995
Accession Number
ADA291717

Entities

People

  • Edward Wegman

Organizations

  • George Mason University

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Computer Science
  • Coordinate Systems
  • Data Analysis
  • Data Sets
  • Estimators
  • Geometric Forms
  • Lines (Geometry)
  • Mathematical Analysis
  • Point Clouds
  • Probability
  • Random Variables
  • Statistics
  • Students
  • Three Dimensional
  • Two Dimensional
  • Visualizations

Readers

  • Academic Conference Management
  • Distributed Systems and Data Platform Development
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms