Recent work in Ontology learning and Text mining has mainly focused on engineering methods to solve practical problem. In this thesis, we investigate methods that can substantially...
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classif...
Cristian Bucila, Rich Caruana, Alexandru Niculescu...
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
— The joint analysis of genetic and brain imaging data is the key to understand the genetic underpinnings of brain dysfunctions in several psychiatric diseases known to have a st...
Johannes Mohr, Imke Puis, Jana Wrase, Sepp Hochrei...