1 In this paper, we propose the use of data mining algorithms to create a macroblock partition mode decision algorithm for inter-frame prediction, to be used as part of a high-effi...
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
Machine learning methods are frequently used to create rule-based classifiers. For continuous features linguistic variables used in conditions of the rules are defined by membershi...
Wlodzislaw Duch, Norbert Jankowski, Krzysztof Grab...
Random forests were introduced as a machine learning tool in Breiman (2001) and have since proven to be very popular and powerful for high-dimensional regression and classificatio...