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...
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
Protein function prediction is an active area of research in bioinformatics. And yet, transfer of annotation on the basis of sequence or structural similarity remains widely used ...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
In the paper a new measure of distance between events/observations in the pattern space is proposed and experimentally evaluated with the use of k-NN classifier in the context of b...
This paper concerns the use of real-valued functions for binary classification problems. Previous work in this area has concentrated on using as an error estimate the `resubstitut...
A process, based on argumentation theory, is described for classifying very noisy data. More specifically a process founded on a concept called “arguing from experience” is des...
Maya Wardeh, Frans Coenen, Trevor J. M. Bench-Capo...
Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to ...
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...