Creating Decision Criteria From Examples: The CRiteria Learning System (Crls)

This thesis describes research on a machine learning approach to automated knowledge acquisition. It focuses on the needs and expectations of problem-solvers in the domain of medicine. It outlines an approach to learning criteria-based knowledge from examples and describes the implementation of a program called the CRiteria Learning System (CRLS) which learns rules in the form of criteria tables. The program learns with a bias for unate (monotone) boolean functions which display non-equivalence symmetry. These biases are described along with their applicability to the problem of learning decision criteria.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Spackman, Kent Alan

Contributors dc:contributor

• Baskin, Arthur B., III

• Education, Technology of
• Computer Science

Identifier

(UMI)AAI8815425

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/69591