I don’t understand why when predicting, the ‘data’ is used but we’re predicting the ‘target’
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Think of it as a target y that is computed as a function f of the data X. Then f is learned during fit and then used to compute y = f(X) during predict, i.e. predict the target (outcome) given the data (input).
That makes more sense, thank you.