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Dirichlet regression is possible in brms using the dirichlet family. But this requires that outcomes be non-zero.
Election outcomes are one case where outcomes are distributed according to the diri…
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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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Για καθε Classification, Regression, Clustering job θα πρεπει να μπορει ο χρηστης να τα παραμετροποιει με καποια συγκεκριμενα attributes.
Tasks:
- [x] Να ενημερωθει η διεπαφη του Process Modelling ωσ…
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La idea de este issue es que dejemos un enlace, nota, imagen, comentario, etc. a recursos que nos encontramos por ahi y pensamos que pueden ser utiles para desarrollar este curso.
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see #2297 for implementation and use
local FDR is based on Efron Statistical Science 2008, with reference to R package
that paper refers to
Efron, Bradley; Tibshirani, Robert. Using specially desig…
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Here are some ideas which could use some discussion and careful consideration. It extends the current model specification: https://lindeloev.github.io/mcp/articles/formulas.html
In the order from "…
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The examples in https://github.com/tensorflow/probability/tree/master/tensorflow_probability/examples do not run with TensorFlow 2, but it's been a while the stable TF2 is available. So, any plans to …
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I have a multiple output regression problem that I want to cross validate with grouped Kfold.
```python
import numpy as np
from flaml import AutoML
from sklearn.multioutput import MultiOutputReg…
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Wishing for a method `l2norm(d::Distribution)` that returns the L2 norm of the probability density function for `d`. Our use case is computing the Brier loss and integrated square loss for machine lea…
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#### Description
Naive bayes in sklearn seems do not support additive smoothing only.
Can we make some change to make it support good-turing smoothing or other smoothing and how?
In some experiment…