In this chapter, we use a search tree structure to efficiently implement a sorted map. The three most fundamental methods of a map M are M[k] implemented with __getitem, M[k] = v using __setitem__ and ...

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning ...

Abstract: Traffic classification is a process which assorts computer network traffic into predefined traffic classes by utilizing packet header information or network packet statistics. Real-time ...

Abstract: Machine learning has been successfully applied to drug combination prediction in recent years. However, in some situations, the class imbalance problem still shows highly negative impacts on ...

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...