previous grade classification, ease of implementation, and potential impacts on the market. In this process, CLASP, with the …

Packaging Group may cover more than one Hazard Zone. If the packaging groups are chosen to correspond to the classification …

the performance with respect to the uncertain and design variables. The proposed algorithm is directly parallelizable and …. The output of this process is utilized by statistical classification procedures in order to derive the dependence of the …

Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an … training data (as in bagging or boosting) and running a conventional tree-building algorithm, or by randomizing the induction … algorithm itself. The objective of this paper is to describe the first experiences with a novel randomized tree induction method …

Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an … training data (as in bagging or arcing) and running a conventional tree-building algorithm, or by randomizing the induction … algorithm itself. The objective of this paper is to describe our first experiences with a novel randomized tree induction method …

objective based classification to farmland owners using the data of Finnish farmland owners. We compare two classification …

uncertainty after model selection. In this work, we propose a novel model-combining algorithm for classification in biomarker … are considered in the article. The weights and algorithm are justified using decision theory and risk-bound results …

design a classifier. In this thesis, we present kernel methods for classification with irregularly sampled and contaminated … more discriminating power than those used by clinicians.Second, we consider one-class classification problem with …