: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Using keyword search to find relevant objects in digital libraries often results in way too large result sets. Based on the metadata associated with such objects, the faceted sear...
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...