We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...