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» Extracting Propositions from Trained Neural Networks
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MICCAI
2000
Springer
13 years 11 months ago
Robust Midsagittal Plane Extraction from Coarse, Pathological 3D Images
Abstract. This paper focuses on the evaluation of an ideal midsagittal plane iMSP extraction algorithm. The algorithm was developed for capturing the iMSP from 3D normal and pathol...
Yanxi Liu, Robert T. Collins, William E. Rothfus
ICAISC
2004
Springer
14 years 23 days ago
Visualizing and Analyzing Multidimensional Output from MLP Networks via Barycentric Projections
Barycentric plotting, achieved by placing gaussian kernels in distant corners of the feature space and projecting multidimensional output of neural network on a plane, provides inf...
Filip Piekniewski, Leszek Rybicki
ANNPR
2006
Springer
13 years 11 months ago
Incremental Training of Support Vector Machines Using Truncated Hypercones
We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
Shinya Katagiri, Shigeo Abe
BMCBI
2005
126views more  BMCBI 2005»
13 years 7 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
CEC
2008
IEEE
14 years 1 months ago
Increasing rule extraction accuracy by post-processing GP trees
—Genetic programming (GP), is a very general and efficient technique, often capable of outperforming more specialized techniques on a variety of tasks. In this paper, we suggest ...
Ulf Johansson, Rikard König, Tuve Löfstr...