A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
: In this paper, we present a novel method for fast data-driven construction of regression trees from temporal datasets including continuous data streams. The proposed Mean Output ...
This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-ofsample future year te...
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...