Title :
Data-driven constructive induction in AQ17-PRE: A method and experiments
Author :
Bloedorn, Eric ; Michalski, Ryszard S.
Author_Institution :
Center for Artificial Intelligence, George Mason Univ., Fairfax, VA, USA
Abstract :
A method is presented for constructive induction, in which new attributes are constructed as various functions of original attributes. Such a method is called data-driven constructive induction, because new attributes are derived from an analysis of the data (examples) rather than the generated rules. Attribute construction and rule generation are repeated until a termination condition, such as the satisfaction of a rule quality measure, is met. The first step of this method, the generation of new attributes, has been implemented in AQ17-PRE. Initial experiments with AQ17-PRE have shown that it leads to an improvement of the learned rules in terms of both their simplicity and their accuracy on testing examples
Keywords :
inference mechanisms; knowledge based systems; learning systems; AQ17-PRE; attribute construction; data-driven constructive induction; rule generation; rule quality measure; Arithmetic; Artificial intelligence; Data analysis; Decision trees; Induction generators; Performance evaluation; Testing;
Conference_Titel :
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-8186-2300-4
DOI :
10.1109/TAI.1991.167073
