@inproceedings{705806dfd926472da3684c0109aaaa73,
title = "Machine learning by multi-feature extraction using genetic algorithms",
abstract = "Constructive Induction methods aim to solve the problem of learning hard concepts despite complex interaction in data. We propose a new Constructive Induction method based on Genetic Algorithms with a non-algebraic representation of features. The advantage of our method to some other similar methods is that it constructs and evaluates a combination of features. Evaluating constructed features together, instead of considering them one by one, is essential when number of interacting attributes is high and there are more than one interaction in concept. Our experiments show the effectiveness of this method to learn such concepts.",
keywords = "constructive induction, complex interactions, genetic algorithms, non-algebraic representation",
author = "Shafti, {Leila S.} and Eduarde P{\'e}rez",
year = "2004",
month = nov,
day = "18",
doi = "10.1007/978-3-540-30498-2_25",
language = "English",
isbn = "9783540238065",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "246--255",
editor = "Christian Lema{\^i}tre and Reyes, {Carlos A.} and Gonz{\'a}lez, {Jes{\'u}s A}",
booktitle = "Advances in Artificial Intelligence -- IBERAMIA 2004",
note = "9th Ibero-American Conference on AI, IBERAMIA 2004 ; Conference date: 22-11-2004 Through 26-11-2004",
}