Abstract: Systems and methods for improving the effectiveness of decision trees are disclosed. In one example, an exemplary method for performing such a task may include: 1) receiving, from at least one computing device, a) a sample, b) a classification assigned to the sample by a decision tree employed by the computing device, and c) identification information for a branch configuration that resulted in the classification, 2) determining that the decision tree incorrectly classified the sample, and then 3) excluding the offending branch configuration from future decision trees. An exemplary method for dynamically adjusting the confidence of decision-tree classifications based on community-supplied data, along with corresponding systems and computer-readable media, are also described.