Ensemble methods are able to improve the predictive performance of many base classifiers.
Up till now, they have been applied to classifiers that predict a single target attribute. Given …

Rule-based classification is considered an important task of data classification. The ant-
mining rule-based classification algorithm, inspired from the ant colony optimization …

The independent variables commonly used to predict the stock price index usually contain
data sampled at different frequencies, and simultaneously, there exist multiple outputs …

Methods for learning decision rules are being successfully applied to many problem
domains, in particular when understanding and interpretation of the learned model is …

The conventional classification task of data mining can be called single-label classification,
since there is a single class attribute to be predicted. This paper addresses a more …

Many classification problems, especially in the field of bioinformatics, are associated with
more than one class, known as multi-label classification problems. In this study, we propose …

Motivation Co-expression of two genes across different conditions is indicative of their
involvement in the same biological process. However, when using RNA-Seq datasets with …

The two most commonly addressed data mining tasks are predictive modelling and
clustering. Here we address the task of predictive clustering, which contains elements of …

Unexpected failures occurring in new cars during the warranty period increase the warranty
costs of car manufacturers along with harming their brand reputation. A predictive …

Methods for learning decision rules are being successfully applied to many problem
domains, especially where understanding and interpretation of the learned model is …