This paper investigates how to adapt standard classification rule learning approaches to subgroup discovery. The goal of subgroup discovery is to find rules describing subsets of the population that… (More)

Machine discovery systems help humans to find natural laws from collections of experimentally collected data. Most of the laws found by existing machine discovery systems describe static situations,… (More)

In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in terms of processes… (More)

Rule learning is typically used for solving class$carion and prediction tasks However; learning of classijcarion rules can be adapred also IO subgroup discovery This paper shows how this can be… (More)

Rule learning is typically used in solving classification and prediction tasks. However, learning of classification rules can be adapted also to subgroup discovery. This paper shows how this can be… (More)

A novel class of applications of predictive clustering trees is addressed, namely ranking. Predictive clustering trees, as implemented in Clus, allow for predicting multiple target variables. This… (More)

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically… (More)

Meta decision trees (MDTs) are a method for combining multiple classifiers. We present an integration of the algorithm MLC4.5 for learning MDTs into the Weka data mining suite. We compare classifier… (More)