University of Michigan - Ann Arbor

In this step, we search for the most optimal values for (hyper)parameters that give the best classification model for the chosen evaluation criterion. For example, we can try a range of values for the "k" parameter in k-nearest neighbor classifier.

Classification Problem Optimization

Which one(s) are examples of "Optimization" in classification problems?

When optimizing a classifier, we can optimize the values/settings of each of the hyperparameters separately from each other. Orthogonalization assumes that hyperparameters are independent of each other.

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