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By Herbert L. Roitblat, Ph.D.

Let’s face it. “Active learning,” where the computer picks the training examples sounds cooler than “passive learning,” where the training examples are chosen randomly. Who wants to think that they are passively sitting by when they can be actively going out and finding responsive documents? But when you get past the feel-good aspects of the name, there are some real advantages to a system based on “passive” random sampling. Predictive coding uses machine learning algorithms to construct computational criteria for separating responsive from non-responsive documents. There are many protocols and algorithms that can be […]

 

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