The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features

The AQ21 program aims to perform natural induction, a process of generating inductive hypotheses in human-oriented forms that are easy to interpret and understand. This is achieved by employing a highly expressive representation language, attributional calculus, whose statements resemble natural lan...

Full description

Saved in:
Bibliographic Details
Published in2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06) pp. 523 - 526
Main Authors Wojtusiak, J., Michalski, R.S., Kaufman, K.A., Pietrzykowski, J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2006
Subjects
Calculus
Clocks
Computer science
Data mining
Decision trees
Induction generators
Machine learning
Natural languages
Optimization methods
Training data
Online AccessGet full text

Cover

More Information
Summary:The AQ21 program aims to perform natural induction, a process of generating inductive hypotheses in human-oriented forms that are easy to interpret and understand. This is achieved by employing a highly expressive representation language, attributional calculus, whose statements resemble natural language descriptions. This paper focuses on the pattern discovery mode of AQ21, which produces attributional rules that capture strong regularities in the data, but may not be fully consistent or complete with regard to the training data. AQ21 integrates several novel features, such as optimizing patterns according to multiple criteria, learning attributional rules with exceptions, generating optimized sets of alternative hypotheses, and handling data with unknown, irrelevant and/or non-applicable meta-values
ISBN:0769527280
9780769527284
ISSN:1082-3409
2375-0197
DOI:10.1109/ICTAI.2006.109