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View Code? Open in Web Editor NEWLocal Interpretable Model-Agnostic Explanations For Time Series Forecast Models
Local Interpretable Model-Agnostic Explanations For Time Series Forecast Models
gh-pages
-> this branch is reserved for building docs
generated by sphinxWrite it!
The notebook test_segmentation
examples should be moved to demo and renamed to -> demo_segmenation.
Examples/demo is a similar term, choose one
add data to project
start = 0
end = 1000
X = dataset_test[0][start :end]
y = dataset_test[1][start :end]
In, e.g., Beijing_Air_Quality_2_5_evaluation_Keras.ipynb
Cell 5
I push a branch docs-build-test (do not merge this branch), which contains HTML built from docs. I cannot create github-pages from this repo, hence I ignore 'Settings/Pages'
To view it:
git checkout origin/doc-build-test
open docs/build/html/index.html
Currently, only scratch of tutorial, feel free to add or request.
Local Mean Evaluation expects segments
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-43-0a14d03652c1> in <module>
5 eval_fn=metrics.mean_squared_error,
6 percentile=90,
----> 7 delta=0.1
8 )
9 scores
/c/Users/Udo/git/ts-mule/tsmule/xai/evaluation.py in analysis_relevance(self, X, y, R, predict_fn, eval_fn, replace_method, percentile, delta)
138 percentile=percentile,
139 )
--> 140 X_percentile = np.array(list(X_percentile))
141
142 X_random = self.perturb(X, R,
/c/Users/Udo/git/ts-mule/tsmule/xai/evaluation.py in perturb(self, X, R, replace_method, percentile, shuffle, delta)
108 else:
109 m = self.mask_percentile(r, percentile)
--> 110 yield self._perturb(x, m, replace_method=replace_method)
111
112
/c/Users/Udo/git/ts-mule/tsmule/xai/evaluation.py in _perturb(x, m, replace_method)
79 """
80 repl_fn = getattr(repl, replace_method)
---> 81 r = repl_fn(x)
82 assert x.shape == m.shape == r.shape
83 z = x * m + r * (1 - m)
TypeError: local_mean() missing 1 required positional argument: 'segments'
New ones (ours)
Old ones (related work)
After the paper is accepted, we will publish it to PyPi
Reference: https://realpython.com/pypi-publish-python-package/
Required:
This task is reserved after the repo is published
We decide to use readthedocs
as a host for documentation, instead of using GitHub pages (administrating limitation)
@merowech
The structure of src/tsmule
should be renamed to tsmule
or src
only because
Another way is to put init.py in src
which way do you prefer?
Currently I have an issue with running tests due to this issue
Cannot merge sub branch from feature/perturbation
to -> sampling
According to
https://github.com/dbvis-ukon/ts-mule/blob/main/demo/beijing_air_2_5/Beijing_Air_Quality_2_5_CNN_explain_Keras.ipynb
the relevance valued at zeros for cnn and dnn models, that is unexpected result.
@merowech Could you please reupload the models?
I am writing the quick-start documents and would like to reuse our pre-trained models to demo and show the usage.
I suggest a structure as we had before :
examples/<data-set-name>/<name_model>.h5
examples/<data-set-name>/<name_testset>.something
In my docs tutorial-> I will
tsmule
to generate explanationstsmule
to evaluate the explanationA declarative, efficient, and flexible JavaScript library for building user interfaces.
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