MDR

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1.2.5 / 2.0 Beta 8.4 GPL (GNU General Public License)    
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MDR was developed to facilitate the detection, characterization, and interpretation of gene-gene interactions or epistasis.

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MDR was developed to facilitate the detection, characterization, and interpretation of gene-gene interactions or epistasis. It uses a novel constructive induction algorithm to detect nonlinear interactions among discrete attributes.

What is MDR?

Multifactor Dimensionality Reduction (MDR) is a nonparametric and genetic model-free alternative to logistic regression for detecting and characterizing nonlinear interactions among discrete genetic and environmental attributes. The MDR method combines attribute selection, attribute construction, classification, cross-validation and visualization to provide a comprehensive and powerful data mining approach to detecting, characterizing, and interpreting nonlinear interactions.

Requirements:

Java Runtime Environment (JRE) 1.5 or later
Java HotSpot Client VM (build 1.4.2_06-b03, mixed mode)

What's New in This Release:

Fix saved analysis output bug. In the '@results' section for each model, where the training and testing confusion matrix are output for each cross validation test, the testing was incorrect -- it was the training confusion matrix repeated rather than the testing matrix. The averages in the line with 'AvgTrain' were correct so the overall training and testing accuracies were still available.

Fix bug where loading an analysis and then re-saving it would cause a null pointer exception.
Simplest fix, although not ideal, was to disable save analysis when an old analysis is loaded.
If a new analysis is run, then the 'Save Analysis' button will be enabled as usual. If a copy of an existing analysis is needed, it can be done outside of MDR.
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Last updated on September 14th, 2011
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