StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
https://doi.org/10.1109/TVCG.2020.3030352
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58 lines
1.2 KiB
58 lines
1.2 KiB
4 years ago
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# gamma
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[gamma function](http://en.wikipedia.org/wiki/Gamma_function)
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in javascript using the
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[lanczos approximation](http://en.wikipedia.org/wiki/Lanczos_approximation)
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for small values and the
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[spouge approximation](https://en.wikipedia.org/wiki/Spouge's_approximation) for
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larger values
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[](http://ci.testling.com/substack/gamma.js)
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[](http://travis-ci.org/substack/gamma.js)
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# example
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```
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> var gamma = require('gamma')
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> gamma(5)
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23.999999999999996
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> gamma(1.6)
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0.8935153492876909
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```
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# methods
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var gamma = require('gamma')
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## gamma(z)
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Return the gamma function over `z`. Complex numbers aren't supported, only reals.
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## gamma.log(z)
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Return the natural log of the gamma function for `z`.
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This function is used internally by the spouge approximation to compute large
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values.
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# install
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With [npm](http://npmjs.org) do:
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```
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npm install gamma
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```
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# kudos
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Implementation transliterated from the python script on the wikipedia entry for
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the
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[lanczos approximation](http://en.wikipedia.org/wiki/Lanczos_approximation).
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Spouge approximation from [Niggler](https://github.com/Niggler).
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# license
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MIT
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