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» Rule Combination in Inductive Learning
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ESWA
2006
122views more  ESWA 2006»
13 years 7 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
GECCO
2007
Springer
214views Optimization» more  GECCO 2007»
14 years 1 months ago
Portfolio allocation using XCS experts in technical analysis, market conditions and options market
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...
Sor Ying (Byron) Wong, Sonia Schulenburg
DOCENG
2006
ACM
14 years 1 months ago
NEWPAR: an automatic feature selection and weighting schema for category ranking
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
Fernando Ruiz-Rico, José Luis Vicedo Gonz&a...
AGENTS
1997
Springer
13 years 11 months ago
A Scalable Comparison-Shopping Agent for the World-Wide Web
The World-Wide-Web is less agent-friendly than we might hope. Most information on the Web is presented in loosely structured natural language text with no agent-readable semantics...
Robert B. Doorenbos, Oren Etzioni, Daniel S. Weld
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
14 years 1 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...