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https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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https://github.com/scikit-learn/scikit-learn/issues/31913 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Aug 10, 2025) ⚠️
**CI failed on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=78962&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Aug 10, 2025)
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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0.0541158... |
https://github.com/scikit-learn/scikit-learn/issues/31912 | [
"RFC",
"Developer API"
] | Stable extender contract via `fit` / `_fit` resp `predict` / `_predict` separation
### Describe the workflow you want to enable
tl;dr, I am suggestion to refactor `scikit-learn` internals to a layer separation with boilerplate between `fit` and `_fit` resp `predict` and `_predict` methods, to make extender interfaces... | 31,912 | [
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https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
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0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31907 | [
"Bug",
"module:cluster"
] | HDBSCAN modifies input precomputed distance matrix
### Describe the bug
When using `sklearn.cluster.HDBSCAN` with `metric="precomputed"`, the input distance matrix is modified after calling `fit_predict()`. The original `hdbscan` package (v0.8.40) works correctly.
### Steps/Code to Reproduce
```py
import numpy as ... | 31,907 | [
-0.021876486018300056,
-0.058209601789712906,
0.0057280766777694225,
-0.051986657083034515,
0.036247193813323975,
0.008229744620621204,
0.016833430156111717,
0.02671178989112377,
0.05310368537902832,
0.00797872245311737,
0.02320464327931404,
-0.020880738273262978,
0.046922631561756134,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31904 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Aug 17, 2025) ⚠️
**CI is still failing on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79126&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Aug 17, 2025)
- Test Collection Failure
C... | 31,904 | [
-0.008708637207746506,
0.044934771955013275,
-0.021536804735660553,
-0.030642099678516388,
0.038679514080286026,
0.005591811146587133,
0.036649227142333984,
0.04611554741859436,
-0.026307253167033195,
0.02724069356918335,
0.048535436391830444,
0.03712007775902748,
-0.0040697259828448296,
0... |
https://github.com/scikit-learn/scikit-learn/issues/31904 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Aug 17, 2025) ⚠️
**CI is still failing on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79126&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Aug 17, 2025)
- Test Collection Failure
C... | 31,904 | [
-0.013440932147204876,
0.041152846068143845,
-0.0337827242910862,
-0.025353550910949707,
0.03362483158707619,
-0.0017025608103722334,
0.03804955258965492,
0.05615401640534401,
-0.009634788148105145,
0.011411336250603199,
0.05274390056729317,
0.05081142485141754,
-0.0067137377336621284,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.06676917523145676,
0.08528205007314682,
0.003737514838576317,
-0.053507160395383835,
0.05103536322712898,
0.008586437441408634,
0.029012326151132584,
0.0920601636171341,
-0.02680964022874832,
-0.009180772118270397,
0.015977242961525917,
0.023810280486941338,
-0.011715012602508068,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.05017366632819176,
0.0640106201171875,
0.007478747051209211,
-0.0516815260052681,
0.08335572481155396,
0.010968590155243874,
0.03640546277165413,
0.08862101286649704,
-0.010131758637726307,
-0.0033767176792025566,
0.003346693003550172,
0.04746844992041588,
-0.020516671240329742,
0.06381... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.05049382895231247,
0.08855298906564713,
0.016839923337101936,
-0.044461388140916824,
0.062307585030794144,
0.0014306912198662758,
0.011945041827857494,
0.08095359802246094,
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-0.018729133531451225,
0.002111515263095498,
0.017094558104872704,
-0.018545569851994514,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.05524591729044914,
0.08592168241739273,
0.002899818355217576,
-0.07456295192241669,
0.052807655185461044,
0.0064916107803583145,
0.0360642746090889,
0.0688692033290863,
-0.015605458989739418,
-0.018045512959361076,
-0.01183249056339264,
0.05111627280712128,
-0.03713865950703621,
0.02771... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.06907462328672409,
0.09066327661275864,
0.006688497960567474,
-0.056463729590177536,
0.051406942307949066,
0.006110033951699734,
0.03258149325847626,
0.08048620820045471,
-0.0342179611325264,
-0.005231533199548721,
0.008161572739481926,
0.029529385268688202,
-0.01632341742515564,
0.0536... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.051146794110536575,
0.08597326278686523,
0.009337863884866238,
-0.04446932673454285,
0.06914030760526657,
0.0031532051507383585,
0.007690147031098604,
0.07432329654693604,
-0.028443576768040657,
-0.01574428752064705,
-0.010982993990182877,
0.03387262672185898,
-0.02361319027841091,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.03858921304345131,
0.09154453873634338,
0.014824427664279938,
-0.045130424201488495,
0.04004095494747162,
-0.002339096972718835,
0.009441583417356014,
0.06917432695627213,
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-0.020109111443161964,
0.008105934597551823,
0.03322218358516693,
-0.02532307617366314,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.05704796686768532,
0.07868892699480057,
0.013734693638980389,
-0.053573235869407654,
0.05683630332350731,
0.011171616613864899,
0.02443769946694374,
0.07178491353988647,
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-0.010130002163350582,
0.019611231982707977,
0.045387156307697296,
-0.025815455242991447,
0.051... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.0487060584127903,
0.07747545838356018,
0.01650071330368519,
-0.05969523638486862,
0.04717463627457619,
-0.01902022399008274,
0.0071736047975718975,
0.0916026383638382,
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0.0021381389815360308,
-0.0005822899984195828,
0.03497600182890892,
-0.012354792095720768,
0.061... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.056146737188100815,
0.07312903553247452,
0.023465851321816444,
-0.05360405147075653,
0.046557340770959854,
-0.011104381643235683,
0.007197471335530281,
0.08553685247898102,
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0.0019288762705400586,
-0.011092158034443855,
0.018931692466139793,
-0.012039955705404282,
... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
-0.0660468339920044,
0.09251279383897781,
0.005536823999136686,
-0.053591206669807434,
0.0451936237514019,
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0.023220481351017952,
0.08758774399757385,
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0.016984345391392708,
0.022639822214841843,
-0.01793767884373665,
0.0560830... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
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0.0585... |
https://github.com/scikit-learn/scikit-learn/issues/31901 | [
"New Feature",
"Needs Triage"
] | QuantileTransformer is incredibly slow
### Describe the workflow you want to enable
This is a feature request to improve performance of the QuantileTransformer. It takes ~60 minutes to fit, uses a huge amount of memory when transforming large non-sparse dataframes with 30M+ rows and 500 columns. It also does not supp... | 31,901 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
-0.050606437027454376,
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-0... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
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-0.03558414801955223,
0.0213158... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
-0.049672286957502365,
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0.02819119393825531,
-0.035452231764793396,
... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
-0.04511915147304535,
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0.0407455712556839,
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0.0031709037721157074,
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0.023633599281311035,
-0.03640742599964142,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
-0.04688108712434769,
0.1291452795267105,
-0.0038158621173352003,
0.03873703256249428,
0.040114838629961014,
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0.0009584198123775423,
0.014775744639337063,
0.024047261103987694,
-0.03889641538262367,
0.0023... |
https://github.com/scikit-learn/scikit-learn/issues/31899 | [
"New Feature"
] | Add `covariance_estimator` to `QuadraticDiscriminantAnalysis`?
### Describe the workflow you want to enable
`LinearDiscriminantAnalysis` has an optional `covariance_estimator` parameter, while the similar `QuadraticDiscriminantAnalysis` does not. QDA is even more sensitive than LDA to covariance estimation.
Would it... | 31,899 | [
-0.045602116733789444,
0.1216544583439827,
-0.0022038519382476807,
0.046408843249082565,
0.04608265310525894,
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0.001863847952336073,
0.0019696918316185474,
0.026025641709566116,
-0.03524305671453476,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31896 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 08, 2025) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/16821604494)** (Aug 08, 2025)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/16821604494) on Aug 08... | 31,896 | [
-0.032160431146621704,
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0.035925231873989105,
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0.02654760703444481,
-0.01380112674087286,
0.08... |
https://github.com/scikit-learn/scikit-learn/issues/31894 | [
"Bug"
] | TunedThreasholdClassiffierCV not understanding `func(y_pred, y_true, ...)` as a valid `scoring`
This code
```py
from sklearn.model_selection import TunedThresholdClassifierCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import sklearn
import numpy as np
sklearn... | 31,894 | [
0.006130312569439411,
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0.055523257702589035,
0.007933787070214748,
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0.028349122032523155,
0.007084265351295471,
0.03392636775970459,
-0.010823296383023262,
0.030312003567814827,
0.058595508337020874,
0.04537271335721016,
0.004... |
https://github.com/scikit-learn/scikit-learn/issues/31894 | [
"Bug"
] | TunedThreasholdClassiffierCV not understanding `func(y_pred, y_true, ...)` as a valid `scoring`
This code
```py
from sklearn.model_selection import TunedThresholdClassifierCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import sklearn
import numpy as np
sklearn... | 31,894 | [
0.006130312569439411,
-0.038924675434827805,
0.055523257702589035,
0.007933787070214748,
0.11141179502010345,
-0.00786014087498188,
0.028349122032523155,
0.007084265351295471,
0.03392636775970459,
-0.010823296383023262,
0.030312003567814827,
0.058595508337020874,
0.04537271335721016,
0.004... |
https://github.com/scikit-learn/scikit-learn/issues/31894 | [
"Bug"
] | TunedThreasholdClassiffierCV not understanding `func(y_pred, y_true, ...)` as a valid `scoring`
This code
```py
from sklearn.model_selection import TunedThresholdClassifierCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import sklearn
import numpy as np
sklearn... | 31,894 | [
0.006130312569439411,
-0.038924675434827805,
0.055523257702589035,
0.007933787070214748,
0.11141179502010345,
-0.00786014087498188,
0.028349122032523155,
0.007084265351295471,
0.03392636775970459,
-0.010823296383023262,
0.030312003567814827,
0.058595508337020874,
0.04537271335721016,
0.004... |
https://github.com/scikit-learn/scikit-learn/issues/31894 | [
"Bug"
] | TunedThreasholdClassiffierCV not understanding `func(y_pred, y_true, ...)` as a valid `scoring`
This code
```py
from sklearn.model_selection import TunedThresholdClassifierCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import sklearn
import numpy as np
sklearn... | 31,894 | [
0.006130312569439411,
-0.038924675434827805,
0.055523257702589035,
0.007933787070214748,
0.11141179502010345,
-0.00786014087498188,
0.028349122032523155,
0.007084265351295471,
0.03392636775970459,
-0.010823296383023262,
0.030312003567814827,
0.058595508337020874,
0.04537271335721016,
0.004... |
https://github.com/scikit-learn/scikit-learn/issues/31894 | [
"Bug"
] | TunedThreasholdClassiffierCV not understanding `func(y_pred, y_true, ...)` as a valid `scoring`
This code
```py
from sklearn.model_selection import TunedThresholdClassifierCV
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification
import sklearn
import numpy as np
sklearn... | 31,894 | [
0.006130312569439411,
-0.038924675434827805,
0.055523257702589035,
0.007933787070214748,
0.11141179502010345,
-0.00786014087498188,
0.028349122032523155,
0.007084265351295471,
0.03392636775970459,
-0.010823296383023262,
0.030312003567814827,
0.058595508337020874,
0.04537271335721016,
0.004... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
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0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
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0.05751712620258331,
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0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
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0.05751712620258331,
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0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
-0.008554064668715,
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0.05751712620258331,
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0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
-0.008554064668715,
0.04759088158607483,
-0.02880040369927883,
0.05751712620258331,
-0.017072247341275215,
-0.02093849703669548,
0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31889 | [
"Bug",
"API",
"module:metrics"
] | We don't support `func(estimator, X, y, ...)` across the board as a scorer
Our documentation [here](https://scikit-learn.org/stable/modules/model_evaluation.html#custom-scorer-objects-from-scratch) states a callable with a `(estimator, X, y)` is a valid scorer. However, it isn't.
In https://github.com/scikit-learn/sc... | 31,889 | [
0.005410885438323021,
0.06166895851492882,
0.06243870407342911,
-0.008554064668715,
0.04759088158607483,
-0.02880040369927883,
0.05751712620258331,
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-0.02093849703669548,
0.0023162788711488247,
0.005904864054173231,
0.07161514461040497,
-0.030989903956651688,
0.047307... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
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-0.027690673246979713,
0.004976541269570589,
0.018981097266077995,
0.029671691358089447,
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0.01275852881371975,
0.013065965846180916,
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0.023420315235853195,
0.05874403193593025,
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-0.011066111735999584,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
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0.018587185069918633,
0.00391521817073226,
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0.025311263278126717,
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0.024381428956985474,
0.08197055757045746,
-0.025406360626220703,
0.002279085572808981,
... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
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0.026043029502034187,
0.017700070515275,
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0.02187059074640274,
0.0022370503284037113,
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0.024480901658535004,
0.06415195018053055,
-0.012446017935872078,
-0.012349992990493774,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
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0.004454806912690401,
0.02348613180220127,
0.031714919954538345,
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0.017646273598074913,
0.025382570922374725,
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0.019161170348525047,
0.05718706548213959,
-0.014265910722315311,
-0.004036078695207834,
-0.052... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
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0.028329631313681602,
0.020790906623005867,
-0.023049630224704742,
0.022195938974618912,
0.003955068066716194,
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0.01998651772737503,
0.06358309835195541,
-0.011921439319849014,
-0.01701687090098858,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
-0.029360832646489143,
-0.0613228864967823,
-0.000970993482042104,
0.023123230785131454,
0.042480163276195526,
-0.028694966807961464,
0.01816442981362343,
0.01943746954202652,
-0.027353204786777496,
0.022500289604067802,
0.05300775542855263,
-0.0008706229273229837,
-0.014916308224201202,
-... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
-0.022295206785202026,
-0.05250899866223335,
0.0036344255786389112,
0.021037891507148743,
0.029112890362739563,
-0.02598227560520172,
0.013116242364048958,
0.018518581986427307,
-0.0245984960347414,
0.026345103979110718,
0.058115795254707336,
-0.006542347837239504,
-0.00750475050881505,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/31885 | [
"Bug",
"Moderate"
] | `SVC(probability=True)` is not thread-safe
This was discovered while running:
```
pytest -v --parallel-threads=4 --iterations=2 sklearn/svm/tests/test_sparse.py
```
before including the fix pushed to #30041 under https://github.com/scikit-learn/scikit-learn/pull/30041/commits/bce2b4eb7d5ab49cf758f98c667e86243883d1d... | 31,885 | [
-0.029637331143021584,
-0.046976473182439804,
-0.008776526898145676,
0.027354009449481964,
0.019836081191897392,
-0.026525339111685753,
0.02150704897940159,
0.008859624154865742,
-0.04854821413755417,
0.02362946793437004,
0.06515947729349136,
-0.010395348072052002,
-0.013927938416600227,
-... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31884 | [
"Bug"
] | pairwise_distances_argmin_min / ArgKMin64 is not thread-safe
### Describe the bug
Problem found while test investigating failures found in #30041. I crafted a minimal reproducer below. It might be caused by a race condition (corruption) of shared intermediate buffers used in OpenMP threads.
Some remarks:
- the prob... | 31,884 | [
-0.026501834392547607,
0.00742245651781559,
0.002305852249264717,
0.04894937574863434,
-0.01505370531231165,
0.00043979359907098114,
0.015158099122345448,
0.023504192009568214,
-0.013901373371481895,
-0.011941112577915192,
0.012255345471203327,
0.03224784880876541,
0.01553954929113388,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31883 | [
"Bug"
] | Fitting different instances of `LinearSVR` is not thread-safe
### Describe the bug
Found while working on #30041.
See the reproducer below. Fitting `LinearSVR` probably relies on a shared global state in the C++ code and that introduces a race condition when fitting several models concurrently in different threads. ... | 31,883 | [
-0.03542350232601166,
0.02984120324254036,
-0.020638462156057358,
0.058583468198776245,
0.039753176271915436,
0.005708340555429459,
0.023475738242268562,
-0.0007587394793517888,
0.022276243194937706,
-0.0003672234888654202,
0.035635899752378464,
0.02540310099720955,
-0.0013151838211342692,
... |
https://github.com/scikit-learn/scikit-learn/issues/31883 | [
"Bug"
] | Fitting different instances of `LinearSVR` is not thread-safe
### Describe the bug
Found while working on #30041.
See the reproducer below. Fitting `LinearSVR` probably relies on a shared global state in the C++ code and that introduces a race condition when fitting several models concurrently in different threads. ... | 31,883 | [
-0.03542350232601166,
0.02984120324254036,
-0.020638462156057358,
0.058583468198776245,
0.039753176271915436,
0.005708340555429459,
0.023475738242268562,
-0.0007587394793517888,
0.022276243194937706,
-0.0003672234888654202,
0.035635899752378464,
0.02540310099720955,
-0.0013151838211342692,
... |
https://github.com/scikit-learn/scikit-learn/issues/31883 | [
"Bug"
] | Fitting different instances of `LinearSVR` is not thread-safe
### Describe the bug
Found while working on #30041.
See the reproducer below. Fitting `LinearSVR` probably relies on a shared global state in the C++ code and that introduces a race condition when fitting several models concurrently in different threads. ... | 31,883 | [
-0.03542350232601166,
0.02984120324254036,
-0.020638462156057358,
0.058583468198776245,
0.039753176271915436,
0.005708340555429459,
0.023475738242268562,
-0.0007587394793517888,
0.022276243194937706,
-0.0003672234888654202,
0.035635899752378464,
0.02540310099720955,
-0.0013151838211342692,
... |
https://github.com/scikit-learn/scikit-learn/issues/31872 | [
"Bug"
] | Strange normalization of semi-supervised label propagation in `_build_graph`
The method `_build_graph` on the `LabelPropagation` class in `sklearn/semi_supervised/_label_propagation.py` [(line 455)](https://github.com/scikit-learn/scikit-learn/blob/7d1d96819172e2a7c826f04c68b9d93188cf6a92/sklearn/semi_supervised/_labe... | 31,872 | [
0.004406487103551626,
-0.05103949084877968,
0.031697992235422134,
0.004503291565924883,
0.019802220165729523,
-0.033379826694726944,
0.028702545911073685,
0.00092834368115291,
-0.03189999982714653,
0.018867528066039085,
-0.015772106125950813,
0.042677272111177444,
0.03790242597460747,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31872 | [
"Bug"
] | Strange normalization of semi-supervised label propagation in `_build_graph`
The method `_build_graph` on the `LabelPropagation` class in `sklearn/semi_supervised/_label_propagation.py` [(line 455)](https://github.com/scikit-learn/scikit-learn/blob/7d1d96819172e2a7c826f04c68b9d93188cf6a92/sklearn/semi_supervised/_labe... | 31,872 | [
0.004406487103551626,
-0.05103949084877968,
0.031697992235422134,
0.004503291565924883,
0.019802220165729523,
-0.033379826694726944,
0.028702545911073685,
0.00092834368115291,
-0.03189999982714653,
0.018867528066039085,
-0.015772106125950813,
0.042677272111177444,
0.03790242597460747,
0.01... |
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