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» Introduction to artificial neural networks
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EVOW
2010
Springer
14 years 2 months ago
Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions
DEODHAR, SUSHAMNA DEODHAR. Using Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions in Genetic Epidemiology. (Under the direction of Dr. Alison Motsinger-Re...
Sushamna Deodhar, Alison A. Motsinger-Reif
MICAI
2004
Springer
14 years 1 months ago
A Biologically Motivated and Computationally Efficient Natural Language Processor
Abstract. Conventional artificial neural network models lack many physiological properties of the neuron. Current learning algorithms are more concerned to computational performanc...
João Luís Garcia Rosa
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
MLDM
2007
Springer
14 years 2 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...
ICANN
2010
Springer
13 years 9 months ago
Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap
Structural equation models have been widely used to study causal relationships between continuous variables. Recently, a non-Gaussian method called LiNGAM was proposed to discover ...
Yusuke Komatsu, Shohei Shimizu, Hidetoshi Shimodai...