Using Iceberg Concept Lattices and Implications Rules to Extract Knowledge from Ann-Reference-Cited by-同舟云学术

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Using Iceberg Concept Lattices and Implications Rules to Extract Knowledge from Ann

Published:2013-08 Issue:3 Volume:19 Page:361-372
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:Intelligent Automation & Soft Computing

Author:

Dias Sérgio M.,Zárate Luis E.,Vieira Newton J.

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Reference27 articles.

1. Rule extraction from local cluster neural nets

2. Are artificial neural networks black boxes?

3. Craven, Mark W. & Shavlik, Jude W. (1995). Extracting comprehensible concept representations from trained neural networks. In Working Notes on the IJCAI ’95 Workshop on Comprehensibility in M.L (pp. 61–75)

4. Tarca, A. L. & Cooke, J. E. K. (2005). A robust neural network approach for spatial and intensity-dependent normalization of CDNA microarray data. Bioinformatics, 21(11), 2674–83

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2. Attribute reduction based on directed graph in formal fuzzy contexts;Journal of Intelligent & Fuzzy Systems;2018-06-22

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