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Machine Learning, 2nd Edition by Stephen Marsland

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Chapter 14

Unsupervised Learning

Many of the learning algorithms that we have seen to date have made use of a training set that consists of a collection of labelled target data, or at least (for evolutionary and reinforcement learning) some scoring system that identifies whether or not a prediction is good or not. Targets are obviously useful, since they enable us to show the algorithm the correct answer to possible inputs, but in many circumstances they are difficult to obtain—they could, for instance, involve somebody labelling each instance by hand. In addition, it doesn’t seem to be very biologically plausible: most of the time when we are learning, we don’t get told exactly what the right answer should be. In this chapter we will consider ...

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