๐Ÿ‘คsshb๐Ÿ•‘9y๐Ÿ”ผ105๐Ÿ—จ๏ธ15

(Replying to PARENT post)

I hate to be a curmudgeon but is machine learning really necessary for a wavelet decompose?

Can anyone give an example where this enables you do to things that couldn't be done better with other techniques?

๐Ÿ‘คenthdegree๐Ÿ•‘9y๐Ÿ”ผ0๐Ÿ—จ๏ธ0

(Replying to PARENT post)

Note that chart appears to not work on iOS, as Plot.ly is erroneously snowing a "Webgl not supported" message (which is an error on their end, as the official website for the library shows the same issue. Issue on GitHub: https://github.com/plotly/plotly.js/issues/280)

That's a shame, as their API is pretty good, as this demo illustrates.

๐Ÿ‘คminimaxir๐Ÿ•‘9y๐Ÿ”ผ0๐Ÿ—จ๏ธ0

(Replying to PARENT post)

I really need to play with the 3d canvas context API...
๐Ÿ‘คartursapek๐Ÿ•‘9y๐Ÿ”ผ0๐Ÿ—จ๏ธ0

(Replying to PARENT post)

I haven't read much on gradient boosting, so questions:

1. Where is the gradient? This explanation makes it sound like a straight Generalized Additive Model.

2. In fact, the explanation makes it sounds worse than random forests. Wouldn't it quickly overfit? Where does the boosting come into play?

๐Ÿ‘คced๐Ÿ•‘9y๐Ÿ”ผ0๐Ÿ—จ๏ธ0