CLASSIFICATION AND DISCRIMINATION IN THE ANALYSIS OF CREDIT RISKS: I.

Abstract

Clustering and classification techniques are introduced for the categorization of credit risks. A metric distance for qualitative characteristics is defined. Some shortcomings of clustering by maximum correlation are discussed. Connections between cluster analysis and algorithms of graph theory and of mathematical programming will be considered in a forthcoming supplement to this report. A second report will deal with discrimination of risk categories. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1968
Accession Number
AD0666809

Entities

People

  • Giandomenico Majone

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Clustering
  • Computer Programming
  • Cooperation
  • Discrimination
  • Evolutionary Algorithms
  • Graph Theory
  • Heuristic Methods
  • Mathematical Programming
  • Mathematics

Readers

  • Aviation Safety Risk Assessment.
  • Computer Vision.
  • Systems Analysis and Design