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4min chapter
Kernel Density Estimation with Seaton Ullberg
Rustacean Station
How Much Weight Should I Give to Katie Versus Like Other Competing Algorithms?
In terms of computational efficiency, it definitely gets hard when you get into more and more dimensions that you're working with. But really from a mathematical standpoint, there's no limit. You could have, you know, a thousand dimensions and it would be still the same techniqueThat is some pretty advanced math. So how much weight should I give to Katie versus like other competing algorithms? Well, it's kind of interesting. It seems like so many people jump straight into AI and these really deep neural networks before they try and apply these simpler statistical techniques.
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