In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
In this paper we apply a machine learning approach to the problem of estimating the number of defects called Regression via Classification (RvC). RvC initially automatically discr...
Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamel...
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
In the present work we study the appropriateness of a number of linear and non-linear regression methods, employed on the task of speech segmentation, for combining multiple phone...