For two-class classification, it is common to classify by setting a threshold on class probability estimates, where the threshold is determined by ROC curve analysis. An analog fo...
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
SuperParent-One-Dependence Estimators (SPODEs) loosen Naive-Bayes’ attribute independence assumption by allowing each attribute to depend on a common single attribute (superpare...
Ying Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey ...