Data-driven theory refinement using KBDistAl

Jihoon Yang, Rajesh Parekh, Vasant Honavar, Drena Dobbs

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Knowledge based artificial neural networks offer an attractive approach to extending or modifying incomplete knowledge bases or domain theories through a process of data-driven theory refinement. We present an efficient algorithm for data-driven knowledge discovery and theory refinement using DistAl, a novel (inter-pattern distance based, polynomial time) constructive neural network learning algorithm. The initial domain theory comprising of propositional rules is translated into a knowledge based network. The domain theory is modified using DistAl which adds new neurons to the existing network as needed to reduce classification errors associated with the incomplete domain theory on labeled training examples. The proposed algorithm is capable of handling patterns represented using binary, nominal, as well as numeric (real-valued) attributes. Results of experiments on several datasets for financial advisor and the human genome project indicate that the performance of the proposed algorithm compares quite favorably with other algorithms for connectionist theory refinement (including those that require substantially more computational resources) both in terms of generalization accuracy and network size.

Original languageEnglish (US)
Title of host publicationAdvances in Intelligent Data Analysis - 3rd International Symposium, IDA 1999, Proceedings
EditorsDavid J. Hand, Joost N. Kok, Michael R. Berthold
PublisherSpringer Verlag
Pages331-342
Number of pages12
ISBN (Print)3540663320, 9783540663324
DOIs
StatePublished - Jan 1 1999
Event3rd International Symposium on Intelligent Data Analysis, IDA 1999 - Amsterdam, Netherlands
Duration: Aug 9 1999Aug 11 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1642
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Symposium on Intelligent Data Analysis, IDA 1999
CountryNetherlands
CityAmsterdam
Period8/9/998/11/99

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Data-driven theory refinement using KBDistAl'. Together they form a unique fingerprint.

Cite this