March 2018
Intermediate to advanced
272 pages
7h 53m
English
Content preview from Deep Learning Quick Reference
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The cost function
We need our classifier to predict the probability of seizure, which is class 1. This means that our output will be constrained to [0,1] as it would be in a traditional logistic regression model. Our cost function, in this case, will binary cross-entropy, which is also known as log loss. If you've worked with classifiers before, this math is likely familiar to you; however, as a refresher, I'll include it here.
The complete formula for log loss looks like this:
This can probably be seen more simply as a set of two functions, one for case and :
When and
When
The log function is used here to result in a monotonic function ...
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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.