Sciweavers

103 search results - page 12 / 21
» Extraction of fuzzy rules from trained neural network using ...
Sort
View
BIOSYSTEMS
2007
115views more  BIOSYSTEMS 2007»
13 years 7 months ago
Evolving fuzzy rules to model gene expression
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Ricardo Linden, Amit Bhaya
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
ESANN
2004
13 years 9 months ago
Neural networks for data mining: constrains and open problems
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Razvan Andonie, Boris Kovalerchuk
MICAI
2010
Springer
13 years 6 months ago
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
Mahdi Tabassian, Reza Ghaderi, Reza Ebrahimpour
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Accelerated search for biomolecular network models to interpret high-throughput experimental data
Background: The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein e...
Suman Datta, Bahrad A. Sokhansanj