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Gradient Boosting Explained in 3D

105 pointsby sshbalmost 9 years ago

4 comments

enthdegreealmost 9 years ago
I hate to be a curmudgeon but is machine learning really necessary for a wavelet decompose?<p>Can anyone give an example where this enables you do to things that couldn&#x27;t be done better with other techniques?
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minimaxiralmost 9 years ago
Note that chart appears to not work on iOS, as Plot.ly is erroneously snowing a &quot;Webgl not supported&quot; message (which is an error on their end, as the official website for the library shows the same issue. Issue on GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;plotly&#x2F;plotly.js&#x2F;issues&#x2F;280" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;plotly&#x2F;plotly.js&#x2F;issues&#x2F;280</a>)<p>That&#x27;s a shame, as their API is pretty good, as this demo illustrates.
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artursapekalmost 9 years ago
I really need to play with the 3d canvas context API...
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cedalmost 9 years ago
I haven&#x27;t read much on gradient boosting, so questions:<p>1. Where is the gradient? This explanation makes it sound like a straight Generalized Additive Model.<p>2. In fact, the explanation makes it sounds worse than random forests. Wouldn&#x27;t it quickly overfit? Where does the boosting come into play?
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