September 2019
Intermediate to advanced
420 pages
10h 29m
English
book
Machine Learning for OpenCV 4 - Second Edition
by Aditya Sharma, Michael Beyeler (USD), Vishwesh Ravi Shrimali, Michael Beyeler
Content preview from Machine Learning for OpenCV 4 - Second Edition
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Knowing the limitations of expectation-maximization
For all its simplicity, expectation-maximization performs incredibly well in a range of scenarios. That being said, there are some potential limitations that we need to be aware of:
- Expectation-maximization does not guarantee that we will find the globally best solution.
- We must know the number of desired clusters beforehand.
- The decision boundaries of the algorithms are linear.
- The algorithm is slow for large datasets.
Let's quickly discuss these potential caveats in a little more detail.
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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.