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The `KernelDensityEstimation` class currently includes the normal distribution approximation bandwidth estimator (see `KernelDensityEstimation::getDefaultBandwith()`) when no bandwidth is passed to th…
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I would like to help cleaning up the code related to kernel density estimation, and if possible also improve it. Is this of any interest, @josef-pkt ? If so, some help getting started would be great!
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**Describe the solution you'd like**
Histogram estimation is not present in skpro. Implement them from scratch using the conditional density estimate finding the optimal binwidth(h) and find th…
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In #10 I discussed making scatter plots and one of the downsides is the extreme overplotting if entire datasets are used. `ggpointdensity` provides an alternative that is between a scatter plot and a…
Aariq updated
1 month ago
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part of #7338
beta, gamma, invgauss and recipinvgauss kernels can be obtained through sccipy's distributions, with appropriate parameterization.
Birnbaum-Saunders (fatiguelife) should also be pos…
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### Describe the bug
I have met an issue when using the class ```sklearn.neighbors.KernelDensity```. The **kernel density estimation (KDE)** works unusually when the kernel width is very small (les…
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### Issues Found
I was trying to run the **05.13-Kernel-Density-Estimation.ipynb** notebook and found multiple issues:
* `AttributeError: Unknown property normed` - when running plots this error cro…
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**Is your feature request related to a problem? Please describe.**
Mean-shift clustering is a common mode/peak-finding method on imaging and other data, common in classical computer vision problems. …
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## TAC:
On-manifold KDE approx products, e.g. `pqr = p * q * r`, where p,q,r are probability densities, and on say SE(3) manifold, or similar.
Note: probability density on manifold here is akin …
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add nodes for Kriging, IDW, Kernel Density, or Spatial Temporal Kernel Density Estimation node