Add BART introductory example #259
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
OriolAbril
reviewed
Dec 21, 2021
OriolAbril
reviewed
Jan 4, 2022
|
Given that we have a new release this should be ready to merge. |
canyon289
approved these changes
Jan 17, 2022
|
It needs to be executed with the new release though. Otherwise the watermark will say beta1 and this notebook won't run on beta1, only >=beta2 |
OriolAbril
force-pushed
the
bart_intro
branch
from
2a055cd to
a7da870
Compare
OriolAbril
approved these changes
Jan 28, 2022
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This notebook includes two examples showing how to use BART in PyMC and also some intuition about how BART works. I tried to keep it light on the technical details related to BART and focus more on its practical features. But I am opne to add further details explaining BART itself or maybe regression trees or whatever you think is necessary to improve the notebook.
Some references are still missing (I will add them soon as part of this PR), at least the seminal bart paper should be linked and also our upcoming CRC press has a chapter about BART (although with the old implementation).
Also I am working with others on an ArxiV preprint that will work as "extended documentation" of BART with more technical details of our particular implementation of bart and it sampler and also more examples to show strength and limitations of BART and the PyMC implementation. Also in future PRs I will like to add one or two more BART notebooks showing other uses and examples.