html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k |
|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/27563 | [
"Bug"
] | sklearn.utils._param_validation.InvalidParameterError: The 'zero_division' parameter of precision_score must be a float among {0.0, 1.0, nan} or a str among {'warn'}. Got nan instead
### Describe the bug
I'm trying to use `precision_score` with `np.nan` for the `zero_division`. It's not working with `cross_val_sco... | 27,563 |
https://github.com/scikit-learn/scikit-learn/issues/27563 | [
"Bug"
] | sklearn.utils._param_validation.InvalidParameterError: The 'zero_division' parameter of precision_score must be a float among {0.0, 1.0, nan} or a str among {'warn'}. Got nan instead
### Describe the bug
I'm trying to use `precision_score` with `np.nan` for the `zero_division`. It's not working with `cross_val_sco... | 27,563 |
https://github.com/scikit-learn/scikit-learn/issues/27563 | [
"Bug"
] | sklearn.utils._param_validation.InvalidParameterError: The 'zero_division' parameter of precision_score must be a float among {0.0, 1.0, nan} or a str among {'warn'}. Got nan instead
### Describe the bug
I'm trying to use `precision_score` with `np.nan` for the `zero_division`. It's not working with `cross_val_sco... | 27,563 |
https://github.com/scikit-learn/scikit-learn/issues/27563 | [
"Bug"
] | sklearn.utils._param_validation.InvalidParameterError: The 'zero_division' parameter of precision_score must be a float among {0.0, 1.0, nan} or a str among {'warn'}. Got nan instead
### Describe the bug
I'm trying to use `precision_score` with `np.nan` for the `zero_division`. It's not working with `cross_val_sco... | 27,563 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27561 | [
"Bug",
"Needs Triage"
] | MLPClassifier: Cannot turn off convergence warning without side effects
### Describe the bug
As [described](https://github.com/scikit-learn/scikit-learn/discussions/27062) by @qrdlgit, it can have sense to use MLPClassifier with small `max_iter` that are always reached. In this case, I get
```
ConvergenceWarning:... | 27,561 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27559 | [
"Documentation"
] | Correctly document linked libraries
### Describe the issue linked to the documentation
When downloading the current wheel for `scikit-learn==1.3.1`, the metadata tell me that the package is subject to the terms of BSD-3-Clause. Unfortunately, this only applies to the package itself. Skimming through the distributed... | 27,559 |
https://github.com/scikit-learn/scikit-learn/issues/27555 | [
"Bug",
"Needs Triage"
] | Louvain community detection fails to recognize sparse matrix instance
### Describe the bug
TypeError being thrown by sknetwork/utils/check.py:130, in check_format(input_matrix, allow_empty)
I don't think this should be happening.
### Steps/Code to Reproduce
```python
from sknetwork.clustering import Louvain, ge... | 27,555 |
https://github.com/scikit-learn/scikit-learn/issues/27547 | [
"Documentation"
] | Modified huber - Bug in the formula
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/sgd.html#mathematical-formulation
1.5.8. Mathematical formulation -> Loss function details -> Modified huber loss
The equation written for huber loss contains a bug. it is written as ... | 27,547 |
https://github.com/scikit-learn/scikit-learn/issues/27547 | [
"Documentation"
] | Modified huber - Bug in the formula
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/sgd.html#mathematical-formulation
1.5.8. Mathematical formulation -> Loss function details -> Modified huber loss
The equation written for huber loss contains a bug. it is written as ... | 27,547 |
https://github.com/scikit-learn/scikit-learn/issues/27547 | [
"Documentation"
] | Modified huber - Bug in the formula
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/sgd.html#mathematical-formulation
1.5.8. Mathematical formulation -> Loss function details -> Modified huber loss
The equation written for huber loss contains a bug. it is written as ... | 27,547 |
https://github.com/scikit-learn/scikit-learn/issues/27545 | [
"Needs Triage"
] | ⚠️ CI failed on Ubuntu_Atlas.ubuntu_atlas ⚠️
**CI is still failing on [Ubuntu_Atlas.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60142&view=logs&j=689a1c8f-ff4e-5689-1a1a-6fa551ae9eba)** (Oct 18, 2023)
- test_logistic_regressioncv_class_weights[65-balanced-weight1]
COMMENT:
## ... | 27,545 |
https://github.com/scikit-learn/scikit-learn/issues/27545 | [
"Needs Triage"
] | ⚠️ CI failed on Ubuntu_Atlas.ubuntu_atlas ⚠️
**CI is still failing on [Ubuntu_Atlas.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60142&view=logs&j=689a1c8f-ff4e-5689-1a1a-6fa551ae9eba)** (Oct 18, 2023)
- test_logistic_regressioncv_class_weights[65-balanced-weight1]
COMMENT:
Clo... | 27,545 |
https://github.com/scikit-learn/scikit-learn/issues/27543 | [
"Bug"
] | Handling 'category' for LightGBM models
### Describe the bug
We should be able to convert some columns in the type 'category' in a DataFrame and let the LightGBM model handle it by itself.
### Steps/Code to Reproduce
```python
import pandas as pd
import numpy as np
from lightgbm import LGBMClassifier
from... | 27,543 |
https://github.com/scikit-learn/scikit-learn/issues/27543 | [
"Bug"
] | Handling 'category' for LightGBM models
### Describe the bug
We should be able to convert some columns in the type 'category' in a DataFrame and let the LightGBM model handle it by itself.
### Steps/Code to Reproduce
```python
import pandas as pd
import numpy as np
from lightgbm import LGBMClassifier
from... | 27,543 |
https://github.com/scikit-learn/scikit-learn/issues/27543 | [
"Bug"
] | Handling 'category' for LightGBM models
### Describe the bug
We should be able to convert some columns in the type 'category' in a DataFrame and let the LightGBM model handle it by itself.
### Steps/Code to Reproduce
```python
import pandas as pd
import numpy as np
from lightgbm import LGBMClassifier
from... | 27,543 |
https://github.com/scikit-learn/scikit-learn/issues/27543 | [
"Bug"
] | Handling 'category' for LightGBM models
### Describe the bug
We should be able to convert some columns in the type 'category' in a DataFrame and let the LightGBM model handle it by itself.
### Steps/Code to Reproduce
```python
import pandas as pd
import numpy as np
from lightgbm import LGBMClassifier
from... | 27,543 |
https://github.com/scikit-learn/scikit-learn/issues/27540 | [
"New Feature"
] | SelectKBest shouldn't raise if k > n_samples
### Describe the workflow you want to enable
Let's say I want to build a logistic regression model with at most 50 features. I could do that with something like this:
``make_pipeline(ColumnTransformer(...OneHotEncoder(), remainder="passthrough"), SelectKBest(k=50), Log... | 27,540 |
https://github.com/scikit-learn/scikit-learn/issues/27540 | [
"New Feature"
] | SelectKBest shouldn't raise if k > n_samples
### Describe the workflow you want to enable
Let's say I want to build a logistic regression model with at most 50 features. I could do that with something like this:
``make_pipeline(ColumnTransformer(...OneHotEncoder(), remainder="passthrough"), SelectKBest(k=50), Log... | 27,540 |
https://github.com/scikit-learn/scikit-learn/issues/27540 | [
"New Feature"
] | SelectKBest shouldn't raise if k > n_samples
### Describe the workflow you want to enable
Let's say I want to build a logistic regression model with at most 50 features. I could do that with something like this:
``make_pipeline(ColumnTransformer(...OneHotEncoder(), remainder="passthrough"), SelectKBest(k=50), Log... | 27,540 |
https://github.com/scikit-learn/scikit-learn/issues/27535 | [
"Performance",
"Needs Decision",
"module:tree",
"Breaking Change",
"cython"
] | Use float32_t for tree.threshold
The features `X` in our standard decision trees are float32, so it would make sense for the threshold of features to also be float32, see https://github.com/scikit-learn/scikit-learn/blob/8ae5f186986667bc3042a36f5d23e352acc40154/sklearn/tree/_tree.pxd#L31
Note that the Cython trees ... | 27,535 |
https://github.com/scikit-learn/scikit-learn/issues/27535 | [
"Performance",
"Needs Decision",
"module:tree",
"Breaking Change",
"cython"
] | Use float32_t for tree.threshold
The features `X` in our standard decision trees are float32, so it would make sense for the threshold of features to also be float32, see https://github.com/scikit-learn/scikit-learn/blob/8ae5f186986667bc3042a36f5d23e352acc40154/sklearn/tree/_tree.pxd#L31
Note that the Cython trees ... | 27,535 |
https://github.com/scikit-learn/scikit-learn/issues/27535 | [
"Performance",
"Needs Decision",
"module:tree",
"Breaking Change",
"cython"
] | Use float32_t for tree.threshold
The features `X` in our standard decision trees are float32, so it would make sense for the threshold of features to also be float32, see https://github.com/scikit-learn/scikit-learn/blob/8ae5f186986667bc3042a36f5d23e352acc40154/sklearn/tree/_tree.pxd#L31
Note that the Cython trees ... | 27,535 |
https://github.com/scikit-learn/scikit-learn/issues/27535 | [
"Performance",
"Needs Decision",
"module:tree",
"Breaking Change",
"cython"
] | Use float32_t for tree.threshold
The features `X` in our standard decision trees are float32, so it would make sense for the threshold of features to also be float32, see https://github.com/scikit-learn/scikit-learn/blob/8ae5f186986667bc3042a36f5d23e352acc40154/sklearn/tree/_tree.pxd#L31
Note that the Cython trees ... | 27,535 |
https://github.com/scikit-learn/scikit-learn/issues/27535 | [
"Performance",
"Needs Decision",
"module:tree",
"Breaking Change",
"cython"
] | Use float32_t for tree.threshold
The features `X` in our standard decision trees are float32, so it would make sense for the threshold of features to also be float32, see https://github.com/scikit-learn/scikit-learn/blob/8ae5f186986667bc3042a36f5d23e352acc40154/sklearn/tree/_tree.pxd#L31
Note that the Cython trees ... | 27,535 |
https://github.com/scikit-learn/scikit-learn/issues/27533 | [
"Enhancement"
] | Better inference of the columns remainder dtype in `transformers_` from `ColumnTransformer`
A typical use case is to fit a `ColumnTransfomrer` on a pandas dataframe such as:
```python
# %%
from sklearn.datasets import load_iris
df, y = load_iris(return_X_y=True, as_frame=True)
# %%
from sklearn.preprocessi... | 27,533 |
https://github.com/scikit-learn/scikit-learn/issues/27533 | [
"Enhancement"
] | Better inference of the columns remainder dtype in `transformers_` from `ColumnTransformer`
A typical use case is to fit a `ColumnTransfomrer` on a pandas dataframe such as:
```python
# %%
from sklearn.datasets import load_iris
df, y = load_iris(return_X_y=True, as_frame=True)
# %%
from sklearn.preprocessi... | 27,533 |
https://github.com/scikit-learn/scikit-learn/issues/27533 | [
"Enhancement"
] | Better inference of the columns remainder dtype in `transformers_` from `ColumnTransformer`
A typical use case is to fit a `ColumnTransfomrer` on a pandas dataframe such as:
```python
# %%
from sklearn.datasets import load_iris
df, y = load_iris(return_X_y=True, as_frame=True)
# %%
from sklearn.preprocessi... | 27,533 |
https://github.com/scikit-learn/scikit-learn/issues/27533 | [
"Enhancement"
] | Better inference of the columns remainder dtype in `transformers_` from `ColumnTransformer`
A typical use case is to fit a `ColumnTransfomrer` on a pandas dataframe such as:
```python
# %%
from sklearn.datasets import load_iris
df, y = load_iris(return_X_y=True, as_frame=True)
# %%
from sklearn.preprocessi... | 27,533 |
https://github.com/scikit-learn/scikit-learn/issues/27531 | [
"Bug",
"Needs Triage"
] | NearestNeighbors.kneighbors returns inaccurate distance
### Describe the bug
Using neighbors.NearestNeighbors I noticed that when finding an exact match, kneighbors _sometimes_ returns a distance > 0. (Although the values I've seen so far have been pretty small ~1e-8 to 1e-9)
At first I thought this was a floati... | 27,531 |
https://github.com/scikit-learn/scikit-learn/issues/27531 | [
"Bug",
"Needs Triage"
] | NearestNeighbors.kneighbors returns inaccurate distance
### Describe the bug
Using neighbors.NearestNeighbors I noticed that when finding an exact match, kneighbors _sometimes_ returns a distance > 0. (Although the values I've seen so far have been pretty small ~1e-8 to 1e-9)
At first I thought this was a floati... | 27,531 |
https://github.com/scikit-learn/scikit-learn/issues/27528 | [
"New Feature"
] | Extra plots in partial dependence plots
### Describe the workflow you want to enable
As discussed in #19410, there has been interest in including additional visualizations along with the partial dependence visualizations. Extra plots would aid in the interpretation of partial dependence plots. It would be low overhea... | 27,528 |
https://github.com/scikit-learn/scikit-learn/issues/27528 | [
"New Feature"
] | Extra plots in partial dependence plots
### Describe the workflow you want to enable
As discussed in #19410, there has been interest in including additional visualizations along with the partial dependence visualizations. Extra plots would aid in the interpretation of partial dependence plots. It would be low overhea... | 27,528 |
https://github.com/scikit-learn/scikit-learn/issues/27528 | [
"New Feature"
] | Extra plots in partial dependence plots
### Describe the workflow you want to enable
As discussed in #19410, there has been interest in including additional visualizations along with the partial dependence visualizations. Extra plots would aid in the interpretation of partial dependence plots. It would be low overhea... | 27,528 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27522 | [
"module:test-suite"
] | Add new estimator checks for sparse arrays to ensure compatibility for third-party libraries
In #27090, we make changes in our tests to check that our estimators are compatible with sparse arrays. However, it does not intend to write common tests through new checks available in `estimator_checks.py`.
We should impl... | 27,522 |
https://github.com/scikit-learn/scikit-learn/issues/27518 | [
"Bug"
] | Inconsistent results with same random seed
### Describe the bug
I'm not sure this is a bug and I couldn't find anything in the issues archive, but I'm seeing an inconsistency between consecutive runs of kmeans.fit, even when setting the same random seed via np.random.seed or random_state. I pinned it down to multit... | 27,518 |
https://github.com/scikit-learn/scikit-learn/issues/27518 | [
"Bug"
] | Inconsistent results with same random seed
### Describe the bug
I'm not sure this is a bug and I couldn't find anything in the issues archive, but I'm seeing an inconsistency between consecutive runs of kmeans.fit, even when setting the same random seed via np.random.seed or random_state. I pinned it down to multit... | 27,518 |
https://github.com/scikit-learn/scikit-learn/issues/27518 | [
"Bug"
] | Inconsistent results with same random seed
### Describe the bug
I'm not sure this is a bug and I couldn't find anything in the issues archive, but I'm seeing an inconsistency between consecutive runs of kmeans.fit, even when setting the same random seed via np.random.seed or random_state. I pinned it down to multit... | 27,518 |
https://github.com/scikit-learn/scikit-learn/issues/27518 | [
"Bug"
] | Inconsistent results with same random seed
### Describe the bug
I'm not sure this is a bug and I couldn't find anything in the issues archive, but I'm seeing an inconsistency between consecutive runs of kmeans.fit, even when setting the same random seed via np.random.seed or random_state. I pinned it down to multit... | 27,518 |
https://github.com/scikit-learn/scikit-learn/issues/27518 | [
"Bug"
] | Inconsistent results with same random seed
### Describe the bug
I'm not sure this is a bug and I couldn't find anything in the issues archive, but I'm seeing an inconsistency between consecutive runs of kmeans.fit, even when setting the same random seed via np.random.seed or random_state. I pinned it down to multit... | 27,518 |
https://github.com/scikit-learn/scikit-learn/issues/27514 | [
"Documentation"
] | Model Persistence doc page could provide clearer actionable recommendations
### Describe the issue linked to the documentation
The [Model Persistence page](https://github.com/scikit-learn/scikit-learn/blob/main/doc/model_persistence.rst) currently discusses many options (pickling, `skops`, ONNX and PMML, but it doe... | 27,514 |
https://github.com/scikit-learn/scikit-learn/issues/27514 | [
"Documentation"
] | Model Persistence doc page could provide clearer actionable recommendations
### Describe the issue linked to the documentation
The [Model Persistence page](https://github.com/scikit-learn/scikit-learn/blob/main/doc/model_persistence.rst) currently discusses many options (pickling, `skops`, ONNX and PMML, but it doe... | 27,514 |
https://github.com/scikit-learn/scikit-learn/issues/27514 | [
"Documentation"
] | Model Persistence doc page could provide clearer actionable recommendations
### Describe the issue linked to the documentation
The [Model Persistence page](https://github.com/scikit-learn/scikit-learn/blob/main/doc/model_persistence.rst) currently discusses many options (pickling, `skops`, ONNX and PMML, but it doe... | 27,514 |
https://github.com/scikit-learn/scikit-learn/issues/27514 | [
"Documentation"
] | Model Persistence doc page could provide clearer actionable recommendations
### Describe the issue linked to the documentation
The [Model Persistence page](https://github.com/scikit-learn/scikit-learn/blob/main/doc/model_persistence.rst) currently discusses many options (pickling, `skops`, ONNX and PMML, but it doe... | 27,514 |
https://github.com/scikit-learn/scikit-learn/issues/27514 | [
"Documentation"
] | Model Persistence doc page could provide clearer actionable recommendations
### Describe the issue linked to the documentation
The [Model Persistence page](https://github.com/scikit-learn/scikit-learn/blob/main/doc/model_persistence.rst) currently discusses many options (pickling, `skops`, ONNX and PMML, but it doe... | 27,514 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27510 | [
"New Feature",
"Needs Triage"
] | GrideSearchCV() has Issue with LSSVM () classification
### Describe the workflow you want to enable
Hi,
I tried to use `GrideSearchCV()` with `LSSVM()` but could not do that , please could you help ?
The code :
The code which i used is from Github romolo code.
[https://github.com/RomuloDrumond/LSSVM](https:/... | 27,510 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27508 | [
"Bug",
"Documentation",
"help wanted"
] | Mention that DBSCAN might modify precomputed sparse distance matrix
### Describe the issue linked to the documentation
[DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) provides a parameter called `metric` which can be assigned the value `precomputed` so that a precomputed dist... | 27,508 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27507 | [
"New Feature",
"Needs Info"
] | adding uncertainty quantifier in the "predict" function for DecisionTreeRegressor
### Describe the workflow you want to enable
The "n_node_samples" in "tree_" attribute tracks the number of samples in the leafs. But there should be a easier way of using this quantity for general users.
I hope the following featur... | 27,507 |
https://github.com/scikit-learn/scikit-learn/issues/27506 | [
"Bug"
] | Test failure in i686 with version 1.3.1
### Describe the bug
During the build of scikit-learn for Fedora Linux, I'm obtaining an error runing the tests in i686. The test that fails is:
`sklearn/tree/tests/test_export.py::test_graphviz_toy`
### Steps/Code to Reproduce
In a i686 machine
```
pytest sklearn/tree... | 27,506 |
https://github.com/scikit-learn/scikit-learn/issues/27506 | [
"Bug"
] | Test failure in i686 with version 1.3.1
### Describe the bug
During the build of scikit-learn for Fedora Linux, I'm obtaining an error runing the tests in i686. The test that fails is:
`sklearn/tree/tests/test_export.py::test_graphviz_toy`
### Steps/Code to Reproduce
In a i686 machine
```
pytest sklearn/tree... | 27,506 |
https://github.com/scikit-learn/scikit-learn/issues/27506 | [
"Bug"
] | Test failure in i686 with version 1.3.1
### Describe the bug
During the build of scikit-learn for Fedora Linux, I'm obtaining an error runing the tests in i686. The test that fails is:
`sklearn/tree/tests/test_export.py::test_graphviz_toy`
### Steps/Code to Reproduce
In a i686 machine
```
pytest sklearn/tree... | 27,506 |
https://github.com/scikit-learn/scikit-learn/issues/27506 | [
"Bug"
] | Test failure in i686 with version 1.3.1
### Describe the bug
During the build of scikit-learn for Fedora Linux, I'm obtaining an error runing the tests in i686. The test that fails is:
`sklearn/tree/tests/test_export.py::test_graphviz_toy`
### Steps/Code to Reproduce
In a i686 machine
```
pytest sklearn/tree... | 27,506 |
https://github.com/scikit-learn/scikit-learn/issues/27506 | [
"Bug"
] | Test failure in i686 with version 1.3.1
### Describe the bug
During the build of scikit-learn for Fedora Linux, I'm obtaining an error runing the tests in i686. The test that fails is:
`sklearn/tree/tests/test_export.py::test_graphviz_toy`
### Steps/Code to Reproduce
In a i686 machine
```
pytest sklearn/tree... | 27,506 |
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