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I am new to machine learning, and I am reading a pair of machine learning books. These references talk about 2 different learning approaches: Prediction and inference, I understand the difference between both of them in supervised learning. Nevertheless, I do not know if inference can be the goal of unsupervised learning algorithms. Whether the answer is yes or not, can you please explain me a bit more about the answer and give me examples?

Many thanks for your time and considerations.

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I will say, the inference is the de facto goal of a clustering method. Reason being, clustering essentially means grouping the features based on a certain characteristic or pattern. Since the target label is absent in a clustering problem, it is the inference that helps the analyst decide or determine the possible label for the clustered group. This label thereafter can be used for any prediction task.

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