Bernard Zenko

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We empirically evaluate several state-of-the-art methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to selecting the best classifier from the ensemble by cross validation. Among state-of-the-art stacking methods, stacking with probability distributions and multi-response linear(More)
We empirically evaluate several state-of-the-art methods for constructing ensembles of classifiers with stacking and show that they perform (at best) comparably to selecting the best classifier from the ensemble by cross validation. We then propose a new method for stacking, that uses multi-response model trees at the meta-level, and show that it(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 ensembles combined with MDTs to bagged and boosted decision trees, and to classifier ensembles combined with other methods: voting and stacking with three(More)
Methods for learning decision rules are being successfully applied to many problem domains, in particular when understanding and interpretation of the learned model is necessary. In many real life problems, we would like to predict multiple related (nominal or numeric) target attributes simultaneously. While several methods for learning rules that predict(More)
In this study, we evaluated the impact of long-term occupational exposure to elemental mercury vapor (Hg0) on the personality traits of ex-mercury miners. Study groups included 53 ex-miners previously exposed to Hg0 and 53 age-matched controls. Miners and controls completed the self-reporting Eysenck Personality Questionnaire and the Emotional States(More)
In this paper we investigate the problem of evaluating ranked lists of biomarkers, which are typically an output of the analysis of high-throughput data. This can be a list of probes from microarray experiments, which are ordered by the strength of their correlation to a disease. Usually, the ordering of the biomarkers in the ranked lists varies a lot if(More)
The aim of this study was an analysis of the relationship between pineal hormone melatonin level and long-term occupational exposure to elemental mercury vapour (Hg) of ex-mercury miners. Melatonin (MEL) is a hormonal product of the pineal gland. Hg accumulation in the pineal gland in ex-miners could modify the synthesis of melatonin and there are no data(More)
Nm23-H1 is one of the most interesting candidate genes for a relevant role in Neuroblastoma pathogenesis. H-Prune is the most characterized Nm23-H1 binding partner, and its overexpression has been shown in different human cancers. Our study focuses on the role of the Nm23-H1/h-Prune protein complex in Neuroblastoma. Using NMR spectroscopy, we performed a(More)