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» Predicting mining activity with parallel genetic algorithms
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ROCAI
2004
Springer
14 years 1 months ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
BMCBI
2005
130views more  BMCBI 2005»
13 years 7 months ago
Some statistical properties of regulatory DNA sequences, and their use in predicting regulatory regions in the Drosophila genome
Background: This paper addresses the problem of recognising DNA cis-regulatory modules which are located far from genes. Experimental procedures for this are slow and costly, and ...
Irina I. Abnizova, Rene te Boekhorst, Klaudia Walt...
BIODATAMINING
2008
140views more  BIODATAMINING 2008»
13 years 7 months ago
Modeling gene-by-environment interaction in comorbid depression with alcohol use disorders via an integrated bioinformatics appr
Background: Comorbidity of Major Depressive Disorder (depression) and Alcohol Use Disorders (AUD) is well documented. Depression, AUD, and the comorbidity of depression with AUD s...
Richard C. McEachin, Benjamin J. Keller, Erika F. ...
CIDM
2009
IEEE
14 years 2 months ago
Evolving decision trees using oracle guides
—Some data mining problems require predictive models to be not only accurate but also comprehensible. Comprehensibility enables human inspection and understanding of the model, m...
Ulf Johansson, Lars Niklasson
CLUSTER
2005
IEEE
14 years 1 months ago
A pipelined data-parallel algorithm for ILP
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly...
Nuno A. Fonseca, Fernando M. A. Silva, Víto...