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Practical Predictive Analytics by Ralph Winters

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Supervised versus unsupervised learning models

We have already discussed the concept of target (dependent) variables and independent variables, or features. Features (or independent variables) are used to describe the relationship with, or to predict values of, a target variable. After defining your independent and depending variables, you will formulate your model. One way to characterize the way in which a model learns from the data, is by classifying it into either a supervised or unsupervised learning model.

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