Approaching the ILP 2005 Challenge: Class-Conditional Bayesian Propositionalization for Genetic Classification

This report presents a statistical propositionalisation approach to relational classification and probability estimation on the genetic ILP Challenge domain. The main di.erence between our and existing propositionalisation approaches is its ability to construct features from categorical attributes with many possible values and in particular the object identi.ers. Our classification and ranking results on the genetic domain are promising but will require further evaluation in comparison with other relational models.

By: Claudia Perlich

Published in: RC23677 in 2005


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