2. The system of claim 1 , wherein the hardware processor is further configured to: assign a first importance weight to the sample based on the outcome of the classification of the sample by the first weak learner and a count of samples that have been used to update the classifier; for each of a second plurality of weak learners, classify the sample using the weak learner, determine an outcome of the classification, and determine an updated error rate of the weak learner based on the first importance weight; select a second weak learner from the second plurality based on the updated error rate of the second weak learner; and update the classifier based on the second weak learner.
2. The system of claim 1 , wherein the hardware processor is further configured to: assign a first importance weight to the sample based on the outcome of the classification of the sample by the first weak learner and a count of samples that have been used to update the classifier; for each of a second plurality of weak learners, classify the sample using the weak learner, determine an outcome of the classification, and determine an updated error rate of the weak learner based on the first importance weight; select a second weak learner from the second plurality based on the updated error rate of the second weak learner; and update the classifier based on the second weak learner. 3. The system of claim 2 , wherein the first importance weight is determined based on a ratio between the count of positive samples and a count of all samples that have been used to update the classifier.