November 2015
Intermediate to advanced
190 pages
4h 11m
English
Content preview from Test Driven Machine LearningBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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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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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.