Rare Category Detection Forest

Rare category detecion RCD aims to discover rare categories in a massive unlabeled data set with the help of a labeling oracle. A challenging task in RCD is to discover rare categories which are concealed by numerous data examples from major categories. Only a few algorithms have been proposed for this issue, most of which are on quadratic or cubic time complexity. In this paper, we propose a novel tree-based algorithm known as RCD-Forest with $$O\varphi n \log {n/s}$$ time complexity and high query efficiency where n is the size of the unlabeled data set. Experimental results on both synthetic and real data sets verify the effectiveness and efficiency of our method.