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scikit-learn
scikit-learn is a widely-used Python module for classic machine learning. It is built on top of SciPy.
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Like xarray, pandas supports attaching arbitrary metadata to DataFrames and persisting it across operations. https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.attrs.html
Dask could pretty easily implement this as well. We'd have a
_Frame.attrsproperty. This would likely returnself._meta.attrs.- We'd verify that
dd.from_pandas(data)correctly extractsattrsfrom `da
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For example, if there is a relationship transaction.session_id -> sessions.id and we are calculating a feature transactions: sessions.SUM(transactions.value) any rows for which there is no corresponding session should be given the default value of 0 instead of NaN.
Of course this should not normally occur, but when it does it seems more reasonable to use the default_value.
`DirectF
with the Power Transformer.
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I see the code
device = ‘cuda’ if torch.cuda.is_available() else ‘cpu’
repeated often in user code. Maybe we should introduce device='auto' exactly for this case?
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Interpret
Yes
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resuming training
How do i resume training for text classification?
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Describe the solution you'd like
We already have AutoARIMA, but it would be nice to also interface ARIMA, either from statsmodels or pmdarima.
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https://igel.readthedocs.io/en/latest/_sources/readme.rst.txt includes a link to the assets/igel-help.gif, but that path is broken on readthedocs.
readme.rst is included as ../readme.rst in the sphinx build.
The gifs are in asses/igel-help.gif
The sphinx build needs to point to the asset directory, absolutely:
.. image:: /assets/igel-help.gif
I haven't made a patch, because I haven't
I think it could be useful, when one wants to plot only e.g. class 1, to have an option to produce consistent plots for both plot_cumulative_gain and plot_roc
At the moment, instead, only plot_roc supports such option.
Thanks a lot
Created by David Cournapeau
Released January 05, 2010
Latest release 2 months ago
- Repository
- scikit-learn/scikit-learn
- Website
- scikit-learn.org
- Wikipedia
- Wikipedia
Bug Report
These tests were run on s390x. s390x is big-endian architecture.
Failure log for helper_test.py