Suppose there are bags of unlabeled data and I try to learn the positive instances from those bags. I know there are lots of bag based classification algorithms but my region of interest is positive instance selection based methods like MI-SVM.
Given the unlabelled data, I try to uncover positive instances as defining the classifier.
I know one of the application of Deterministic Annealing to Multiple instance learning over Random Forests.
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