Fuzzy ID3: Evaluation, Rule Generation and Network Mapping.

Date of Submission

December 2000

Date of Award

Winter 12-12-2001

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Machine Intelligence Unit (MIU-Kolkata)


Mitra, Sushmita (MIU-Kolkata; ISI)

Abstract (Summary of the Work)

A fuzzy knowledge-based neural network is generated using rules extracted from fuzzy ID3. The fuzzy decision tree can handle numeric features and/or linguistic features and class membership values, while fuzzy entropy is used at the node level. A new measure is developed to evaluate the goodness of the decision tree. Linguistic rules are extracted and quantitatively evaluated. An optimal fuzzy knowledge-based network is automatically generated using the extracted rules. The effectiveness of the system, in terms of recognition score, performance of rules and size of network, is demonstrated on a vowel recognition problem.


ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843233

Control Number


Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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