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Test-Driven Machine Learning by Justin Bozonier

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Different approaches to validating the improved models

Model quality validation, of course, depends upon the kinds of models that you're building, and the purpose of them. There are a few general types of machine learning problems that I've covered in this book, and each has different ways of validating model quality.

Classification overview

We'll get to the specifics in just a moment, but let's review the high-level terms. One method for quantifying the quality of a supervised classification is using ROC curves. These can be quantified by finding the total area under the curve (AUC), finding the location of the inflection point, or by simply setting a limit of the amount of data that must be classified correctly against percentage of the time. ...

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