This paper addresses the training of classification trees for weakly labelled data. We call ”weakly labelled data”, a training set such as the prior labelling information pro...
This paper describes a new approach, HIDER (HIerarchical DEcision Rules), for learning rules in continuous and discrete domains based on evolutive algorithms. The algorithm produce...
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
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...
We propose a new framework of explanation-oriented data mining by adding an explanation construction and evaluation phase to the data mining process. While traditional approaches c...