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The goal of this issue is to describe the future global refactoring of the package.
The aim of this refactoring is to :
- Modularize the package
- Leverage modularization to enable scikit lear…
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Python libraries for calculating your own kernel density estimate:
http://stackoverflow.com/questions/33274506/kernel-density-estimation-in-seaborn-for-cyclic-end-points
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We have experienced some issues with statsmodels' KDE implementation (see in-line comments in `ridgeplot._kde.estimate_density_trace()`.
- statsmodels uses scipy under the hood. This could be a goo…
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A wishlist for probabilistic regression methods to implement or interface.
This is partly copied from the list I made when designing the R counterpart https://github.com/mlr-org/mlr3proba/issues/32 .…
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The library currently has no support for items like histograms (1D or 2D), bar charts, contour plots, or even regular line plots with error bars.
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Hiya! Mac M1/M2/... are not compatible with CUDA, and so KeOps does not work. I keep getting
```
[KeOps] Warning : Cuda libraries were not detected on the system or could not be loaded ; using cpu …
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Is there any support for KDE (Kernel Density Estimation) based outlier detection planned?
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Add a scatter density method to the Pitch classes.
Inspiration:
- https://twitter.com/etmckinley/status/1169256582145703937
- https://github.com/LKremer/ggpointdensity
In principle, this could…
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This should help us lower the storage requirement of Kernel Density estimation from `n^2`.
Ref: https://github.com/rapidsai/cuml/pull/4545
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Utilize kernel density estimation to estimate the probability distribution or some similar method and utilize that to run simulations