Research article summary (published 30 Jan 2006):

Neuro-fuzzy decision trees.

Full Abstract

Fuzzy decision trees are powerful, top-down, hierarchical search methodology to extract human interpretable classification rules. However, they are often criticized to result in poor learning accuracy. In this paper, we propose Neuro-Fuzzy Decision Trees (N-FDTs); a fuzzy decision tree structure with neural like parameter adaptation strategy. In the forward cycle, we construct fuzzy decision trees using any of the standard induction algorithms like fuzzy ID3. In the feedback cycle, parameters of fuzzy decision trees have been adapted using stochastic gradient descent algorithm by traversing back from leaf to root nodes. With this strategy, during the parameter adaptation stage, we keep the hierarchical structure of fuzzy decision trees intact. The proposed approach of applying backpropagation algorithm directly on the structure of fuzzy decision trees improves its learning accuracy without compromising the comprehensibility (interpretability). The proposed methodology has been validated using computational experiments on real-world datasets.

Author information

Author/s: Bhatt, Rajen B (RB); Gopal, M (M);

Affiliation: Control Laboratories, II/214, Department of Electrical Engineering, Indian Institute of Technology - Delhi, Hauz Khas, New Delhim - 110016, India. rajen.bhatt(-atsign-)gmail.com

Journal and publication information

Publication Type: Journal Article

Journal: International journal of neural systems (Int J Neural Syst), published in Singapore. (Language: eng)

Reference: 2006-Feb; vol 16 (issue 1) : pp 63-78

Dates: Created 2006/02/23; Completed 2006/05/25; Revised 2006/10/11;

PMID: 16496439, status: MEDLINE (last retrieved date: 2/18/2009)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

Comments and Corrections

ErratumIn: Int J Neural Syst. 2006 Aug;16(4):319.

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MeSH headings (categories)

This article was linked to the MeSH Headings (categories) shown below.

Decision Making, Computer-Assisted Decision Trees Fuzzy Logic Humans

Information Storage and Retrieval Learning - physiology Neural Networks (Computer) Neurons - physiology

Note: Bold headings indicate primary MeSH headings or qualifiers.

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