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(going a bit in circles)
- Bernstein polynomial density estimation is a kind of kernel estimation based on histogram data, or grouped probabilities. domain is interval [0,1] #7296
- in fast kde w…
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Is there any support for KDE (Kernel Density Estimation) based outlier detection planned?
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Perhaps estimating the kernel with the kernel density estimation could provide better results than with an histogram, either in the parametric or non parametric case, as shown in:
https://www.ethz.c…
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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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I took some time to look into @yquilcaille's [`distrib_cov._get_weights_nll`](https://github.com/MESMER-group/mesmer/blob/2b5da4a9f5f450c2b01f8e5e64a97eb35dd99d47/mesmer/mesmer_x/train_l_distrib_mesme…
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Utilize kernel density estimation to estimate the probability distribution or some similar method and utilize that to run simulations
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No. You should not use functions provided in a given library or package that will **significantly simplify** the
algorithms that you are asked to implement in coursework, if that is the case, you w…
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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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Hello. I'm trying to understand density-ratio estimation including RuLSIF for implementing transition detection w.r.t. smart home data. Thank you for making such useful module.
As written in the Ru…
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- The theory help page may mention the correct reference for the `computePluginBandwidth` algorithm:
http://openturns.github.io/openturns/master/theory/data_analysis/kernel_smoothing.html
This …