Constructive Induction: Covering Attribute Spectrum

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Inductive algorithms rely strongly on their representational biases. Representational inadequacy can be mitigated by constructive induction. This chapter introduces several important issues for constructive induction and describes a new multi-strategy constructive induction algorithm (GALA2.0) which is independent of the learning algorithm. Unlike most previous research on constructive induction, our methods are designed as a preprocessing step before standard machine learning algorithms are applied. We present the results which demonstrate the effectiveness of GALA2.0 on real domains for two different learners: C4.5 and backpropagation.
Original languageEnglish
Title of host publicationFeature Extraction, Construction and Selection
Place of PublicationBoston
PublisherSpringer
Chapter16
Pages257-272
Number of pages16
ISBN (Electronic)978-1-4615-5725-8
ISBN (Print)978-1-4613-7622-4
DOIs
StatePublished - 1998

Publication series

NameThe Springer International Series in Engineering and Computer Science
PublisherSpringer
Volume453

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