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In terms of functionality, the mid-term end goal is to achieve an offering of ML algorithms and pre-processing routines comparable to what is currently available in Python's [`scikit-learn`](https://s…
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While making these examples using generated random data so I could make these examples public I learned that
```python
from numpy import random
random.seed(0)
```
[is considered bad](https://…
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Hey. Did you compare with SGDClassifier?
The results should be quite close to yours.
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We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.…
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@zoq @rcurtin I felt that this is a fantastic project where people can find which ml-toolkits are better for certain algorithms, and where the toolkits can improve themselves. So, I have been doing …
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### Describe the workflow you want to enable
As partial dependence of a model at a point [is defined as an expectation](https://scikit-learn.org/stable/modules/partial_dependence.html#mathematical-de…
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Hi There,
During our research, we keep having to compare different pipelines or feature sets, and comparing improvement in numerical accuracy is not the best way for few reasons. Testing for signif…
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If others have the time, I'm inclined to experiment a bit with algorithms for distributed training. I think that this would be an interesting stress test of the technology, and would also, I think, r…
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### Describe the workflow you want to enable
I want to enable the workflow of training a `LogisticRegression` model on sparse data, with substantial numbers of features and classes, with acceptable…
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I did some follow-up work for the discussions on potential problems for `Ridge(normalize=False)` in #19426 and #17444 in the following gist:
https://gist.github.com/ogrisel/cf7ac8bca6725ec02d4cc8d0…