Some General Principles for the Dual Problem to Statistical Classification.

Abstract

We consider the design of decision problems which maximize the classification error for a given set of discriminants. A minimax principle is proved, which has applications in discriminant analysis and feature extraction. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 26, 1980
Accession Number
ADA094726

Entities

People

  • Lee K. Jones

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Classification
  • Communication Channels
  • Convex Programming
  • Convex Sets
  • Defense Systems
  • Detectors
  • Electrical Engineering
  • Engineering
  • Feature Extraction
  • Feature Selection
  • Probability
  • Quadratic Programming
  • Radar Signatures
  • Random Variables
  • Standards
  • Stationary
  • Theorems

Readers

  • Calculus or Mathematical Analysis
  • Computer Vision.
  • Regression Analysis.

Technology Areas

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