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BART: improve sampling #5229

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Merged
merged 3 commits into from
Nov 30, 2021
Merged

BART: improve sampling #5229

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0167c88
improves sampling by redrawing leafs and increasing particles
aloctavodia Nov 30, 2021
f023e32
remove linear and mix response
aloctavodia Nov 30, 2021
45d5afb
update release notes
aloctavodia Nov 30, 2021
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2 changes: 1 addition & 1 deletion RELEASE-NOTES.md
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Expand Up @@ -93,9 +93,9 @@ This includes API changes we did not warn about since at least `3.11.0` (2021-01
- `pm.DensityDist` can now accept an optional `logcdf` keyword argument to pass in a function to compute the cummulative density function of the distribution (see [5026](https://github.com/pymc-devs/pymc/pull/5026)).
- `pm.DensityDist` can now accept an optional `get_moment` keyword argument to pass in a function to compute the moment of the distribution (see [5026](https://github.com/pymc-devs/pymc/pull/5026)).
- New features for BART:
- Added linear response, increased number of trees fitted per step [5044](https://github.com/pymc-devs/pymc3/pull/5044).
- Added partial dependence plots and individual conditional expectation plots [5091](https://github.com/pymc-devs/pymc3/pull/5091).
- Modify how particle weights are computed. This improves accuracy of the modeled function (see [5177](https://github.com/pymc-devs/pymc3/pull/5177)).
- Improve sampling, increase default number of particles [5229](https://github.com/pymc-devs/pymc3/pull/5229).
- `pm.Data` now passes additional kwargs to `aesara.shared`. [#5098](https://github.com/pymc-devs/pymc/pull/5098)
- ...

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5 changes: 0 additions & 5 deletions pymc/bart/bart.py
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Expand Up @@ -67,9 +67,6 @@ class BART(NoDistribution):
k : float
Scale parameter for the values of the leaf nodes. Defaults to 2. Recomended to be between 1
and 3.
response : str
How the leaf_node values are computed. Available options are ``constant`` (default),
``linear`` or ``mix``.
split_prior : array-like
Each element of split_prior should be in the [0, 1] interval and the elements should sum to
1. Otherwise they will be normalized.
Expand All @@ -84,7 +81,6 @@ def __new__(
m=50,
alpha=0.25,
k=2,
response="constant",
split_prior=None,
**kwargs,
):
Expand All @@ -103,7 +99,6 @@ def __new__(
m=m,
alpha=alpha,
k=k,
response=response,
split_prior=split_prior,
),
)()
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