Classification Techniques for Multivariate Data Analysis.

Abstract

The multivariate analysis techniques of cluster analysis, principal components analysis, and discriminant analysis are examined in this thesis. The theory and applications of each of the techniques are discussed. Computer software available at the Naval Postgraduate School is discussed and sample jobs are included. A hierarchical cluster analysis algorithm, available in the IMSL software package, is applied to a set of data extracted from a group of subjects for the purpose of partitioning a collection of 26 attributes of a weapon system into six clusters of superattributes. A nonhierarchical clustering procedure, principal components analysis, and discriminant analysis were all applied to a collection of data on tanks consisting of twenty-four observations of ten attributes of tanks. The cluster analysis shows that the tanks cluster somewhat naturally by nationality. The principal components analysis and the discriminant analysis show that tank weight is the single most important discriminator among nationality. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 28, 1980
Accession Number
ADA086521

Entities

People

  • Jin Ki Lee

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computer Programs
  • Computers
  • Data Analysis
  • Data Mining
  • Data Science
  • Discriminant Analysis
  • Factor Analysis
  • Information Science
  • Multivariate Analysis
  • Network Science
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Test And Evaluation
  • Weapon Systems

Readers

  • Computer Science.
  • Regression Analysis.