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 ...
The present paper studies the influence of two distinct factors on the performance of some resampling strategies for handling imbalanced data sets. In particular, we focus on the n...
In this work we present a novel approach to predict the function of proteins in protein-protein interaction (PPI) networks. We classify existing approaches into inductive and tran...
An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-...
— To effectively navigate in their environments and accurately reach their target locations, mobile robots require a globally consistent map of the environment. The problem of le...