Internal Load Balancer for Tree-Based Ensemble Classifiers

摘要

Techniques for implementing a tree-based ensemble classifier comprising an internal load balancer are provided. In one set of embodiments, the tree-based ensemble classifier can receive a query data instance and select, via the internal load balancer, a subset of its decision trees for processing the query data instance. The tree-based ensemble classifier can then query each decision tree in the selected subset with the query data instance, combine the per-tree classifications generated by the subset trees to generate a subset classification, and determine whether a confidence level associated with the subset classification is sufficiently high. If the answer is yes, the tree-based ensemble classifier can output the subset classification as a final classification result for the query data instance. If the answer is no, the tree-based ensemble classifier can repeat the foregoing steps until a sufficient confidence level is reached or until all of its decision trees have been selected and queried.