We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
XCS with Computed Action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed wi...
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...