Difference between revisions of "Talk:2048: Curve-Fitting"
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I'm a little mystified by the alt-text. Cauchy and Lorentz both seem like mathematically capable people. What am I missing? [[Special:Contributions/172.69.62.226|172.69.62.226]] 17:46, 19 September 2018 (UTC) | I'm a little mystified by the alt-text. Cauchy and Lorentz both seem like mathematically capable people. What am I missing? [[Special:Contributions/172.69.62.226|172.69.62.226]] 17:46, 19 September 2018 (UTC) | ||
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| + | : Google-Fu reveals that it's a continuous probability distribution. This isn't bad per se, but it is quite visually distinctive and also can be quite...concerning if the data set isn't one where probability should be an issue. | ||
Revision as of 18:00, 19 September 2018
> House of Cards: Not a real method, but a common consequence of mis-application of statistical methods: a curve can be generated that fits the data extremely well, but immediately becomes absurd as soon as one glances outside the training data sample range, and your analysis comes crashing down "like a house of cards". This is a type of _overfitting_
I'm pretty sure it refers to the TV show house of cards, the dots representing the quality of the series increasing until Netflix renewed it a bit too much
I'm a little mystified by the alt-text. Cauchy and Lorentz both seem like mathematically capable people. What am I missing? 172.69.62.226 17:46, 19 September 2018 (UTC)
- Google-Fu reveals that it's a continuous probability distribution. This isn't bad per se, but it is quite visually distinctive and also can be quite...concerning if the data set isn't one where probability should be an issue.
