Conversation
Owner
|
Let's stick to a neutral naming as discussed in #10 . integrated mean might also work. |
alpiges
commented
Aug 26, 2025
| # kernel and measure must be set first | ||
| self._mean_func_1d = self._get_1d_funcs() | ||
| self._mean_func_1d = self._get_1d_mean_funcs() | ||
| self._var_func_1d = self._get_1d_var_funcs() |
Collaborator
Author
There was a problem hiding this comment.
The issue regarding the tests is here. By passing the function handle, the function is run. This would be fine if we new that for each kernel mean embedding, we also know the integrated kernel mean. But I don't believe that's the case. I would therefore propose to delete these lines, and rename the _get_1d_funcs directly to _mean_func_1d and _var_func_1d.
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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Addressing #10
This PR contains the integrated expquad kernel mean against lebesgue as a starting point for design discussions. Since the
KernelEmbeddinghas amean, it felt natural to add it there as avariance, despite our discussions that "expected kernel mean" might be more appropriate.Still missing: tests for multi-D support
EDIT: When I leave the
ValueErrorin the_get_1d_var_funcsfunction, the tests fail when testing the embedding. This behavior is quite cryptic to me, since this function is not called anywhere. To be investigated.