Accession Number:

ADA343512

Title:

Comparing Simplification Procedures for Decision Trees on an Economics Classification

Descriptive Note:

Final rept.

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC CENTER FOR APPLIED RESEARCH AND ARTIFICIAL INTELLIGENCE

Personal Author(s):

Report Date:

1998-05-11

Pagination or Media Count:

22.0

Abstract:

Several commercial case-based reasoning CBR shells now use decision trees to index cases, including Remind Cognitive Systems, Inc., Kate AcknoSoft, and The Easy Reasoner The Haley Enterprise. These trees serve to expedite case retrieval and to generate comprehensible explanations of case retrieval behavior. Unfortunately, induced trees are often large and complex, reducing their explanatory power. To combat this problem, some commercial systems contain an option for simplifying decision trees. However, while many methods for simplifying decision trees exist, they have not been systematically compared and most have not been applied to case retrieval. This report builds on our previous survey and initial empirical comparison of tree simplification procedures. In this report, we compare them on a specific, challenging task that is the focus of an existing CBR effort. We examine which tree simplification procedures are useful for this task and suggest which ones should be included in a commercial CBR tool.

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE