1. A method of machine learning, comprising: (a) obtaining a training set that includes training samples and corresponding assigned classification labels; (b) training an automated classifier against the training set; (c) selecting at least one of the training samples; (d) requesting confirmation/re-labeling of said at least one training sample; (e) in response to step (d), receiving a reply classification label for said at least one training sample; (f) retraining the automated classifier using the reply classification label; and, predicting a label for said at least one training sample, wherein said at least one training sample is selected in step (c) based on a comparison between the assigned classification label and the predicted label for said at least one training sample.