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/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27368 | [
"New Feature"
] | allow uniform intialization for BayesianGaussianMixture with dirichlet_process wight prior
### Describe the workflow you want to enable
I would like to have a deterministic version of the Bayesian Gaussian Mixture Model
### Describe your proposed solution
I propose allowing for unifrom responsibility initialization... | 27,368 |
https://github.com/scikit-learn/scikit-learn/issues/27368 | [
"New Feature"
] | allow uniform intialization for BayesianGaussianMixture with dirichlet_process wight prior
### Describe the workflow you want to enable
I would like to have a deterministic version of the Bayesian Gaussian Mixture Model
### Describe your proposed solution
I propose allowing for unifrom responsibility initialization... | 27,368 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27363 | [
"Needs Decision"
] | Please start following semver guidelines
### Describe the bug
Hey all, I'm a bit new to skikit-learn, but have built and used many tools that follow semver. I didn't really see anything in the documentation saying that this _isn't_ using semver, but I've noticed breaking changes without a major version bump, which ... | 27,363 |
https://github.com/scikit-learn/scikit-learn/issues/27362 | [
"Bug",
"Needs Triage"
] | Redundant DataConversionWarning in BaseForest
### Describe the bug
A column vector is expected in `*Forest` even though the `y` is reshaped to be 2D:
```
y = np.atleast_1d(y)
if y.ndim == 2 and y.shape[1] == 1:
warn(
(
"A column-vector y was pass... | 27,362 |
https://github.com/scikit-learn/scikit-learn/issues/27362 | [
"Bug",
"Needs Triage"
] | Redundant DataConversionWarning in BaseForest
### Describe the bug
A column vector is expected in `*Forest` even though the `y` is reshaped to be 2D:
```
y = np.atleast_1d(y)
if y.ndim == 2 and y.shape[1] == 1:
warn(
(
"A column-vector y was pass... | 27,362 |
https://github.com/scikit-learn/scikit-learn/issues/27360 | [
"Documentation",
"Needs Triage"
] | Documentation improvement for make_sparse_spd_matrix
### Describe the issue linked to the documentation
I have noticed that the make_sparse_spd_matrix function in scikit-learn's documentation states that it should return a sparse matrix. However, the function currently returns a dense numpy.ndarray. This seems to b... | 27,360 |
https://github.com/scikit-learn/scikit-learn/issues/27359 | [
"Documentation"
] | `make_sparse_spd_matrix` does not return sparse matrix
### Describe the bug
I have been looking at https://github.com/scikit-learn/scikit-learn/issues/27090 and working on `test_graphical_lasso.py`. There is used `make_sparse_spd_matrix` function, which, according to documentation, should return sparse matrix. But it... | 27,359 |
https://github.com/scikit-learn/scikit-learn/issues/27359 | [
"Documentation"
] | `make_sparse_spd_matrix` does not return sparse matrix
### Describe the bug
I have been looking at https://github.com/scikit-learn/scikit-learn/issues/27090 and working on `test_graphical_lasso.py`. There is used `make_sparse_spd_matrix` function, which, according to documentation, should return sparse matrix. But it... | 27,359 |
https://github.com/scikit-learn/scikit-learn/issues/27358 | [
"Documentation",
"module:kernel_approximation"
] | DOC Improve description of the Nystroem method in the user guide
### Describe the issue linked to the documentation
We currently have a rather short and shallow description of the [Nystroem Method for Kernel Approximation](https://scikit-learn.org/stable/modules/kernel_approximation.html#nystroem-method-for-kernel-ap... | 27,358 |
https://github.com/scikit-learn/scikit-learn/issues/27358 | [
"Documentation",
"module:kernel_approximation"
] | DOC Improve description of the Nystroem method in the user guide
### Describe the issue linked to the documentation
We currently have a rather short and shallow description of the [Nystroem Method for Kernel Approximation](https://scikit-learn.org/stable/modules/kernel_approximation.html#nystroem-method-for-kernel-ap... | 27,358 |
https://github.com/scikit-learn/scikit-learn/issues/27358 | [
"Documentation",
"module:kernel_approximation"
] | DOC Improve description of the Nystroem method in the user guide
### Describe the issue linked to the documentation
We currently have a rather short and shallow description of the [Nystroem Method for Kernel Approximation](https://scikit-learn.org/stable/modules/kernel_approximation.html#nystroem-method-for-kernel-ap... | 27,358 |
https://github.com/scikit-learn/scikit-learn/issues/27358 | [
"Documentation",
"module:kernel_approximation"
] | DOC Improve description of the Nystroem method in the user guide
### Describe the issue linked to the documentation
We currently have a rather short and shallow description of the [Nystroem Method for Kernel Approximation](https://scikit-learn.org/stable/modules/kernel_approximation.html#nystroem-method-for-kernel-ap... | 27,358 |
https://github.com/scikit-learn/scikit-learn/issues/27356 | [
"Documentation"
] | Building from source fails using conda instructions
### Describe the bug
I am trying to build the development version of scikit-learn in Windows Subsystem for Linux running Ubuntu 20.04.5 and conda 23.7.2.
After creating the environment, building scikit-learn fails as cython is not found for some reason.
### ... | 27,356 |
https://github.com/scikit-learn/scikit-learn/issues/27356 | [
"Documentation"
] | Building from source fails using conda instructions
### Describe the bug
I am trying to build the development version of scikit-learn in Windows Subsystem for Linux running Ubuntu 20.04.5 and conda 23.7.2.
After creating the environment, building scikit-learn fails as cython is not found for some reason.
### ... | 27,356 |
https://github.com/scikit-learn/scikit-learn/issues/27356 | [
"Documentation"
] | Building from source fails using conda instructions
### Describe the bug
I am trying to build the development version of scikit-learn in Windows Subsystem for Linux running Ubuntu 20.04.5 and conda 23.7.2.
After creating the environment, building scikit-learn fails as cython is not found for some reason.
### ... | 27,356 |
https://github.com/scikit-learn/scikit-learn/issues/27356 | [
"Documentation"
] | Building from source fails using conda instructions
### Describe the bug
I am trying to build the development version of scikit-learn in Windows Subsystem for Linux running Ubuntu 20.04.5 and conda 23.7.2.
After creating the environment, building scikit-learn fails as cython is not found for some reason.
### ... | 27,356 |
https://github.com/scikit-learn/scikit-learn/issues/27350 | [
"Bug",
"Needs Triage"
] | Problem in function "balanced_accuracy_score" calculation.
### Describe the bug
Hi all I am facing a problem in reproducing the `balanced_accuracy_score` function.
Many resources converges on the equation of balanced accuracy as we can see in the link https://www.statology.org/balanced-accuracy-python-sklearn/. ... | 27,350 |
https://github.com/scikit-learn/scikit-learn/issues/27350 | [
"Bug",
"Needs Triage"
] | Problem in function "balanced_accuracy_score" calculation.
### Describe the bug
Hi all I am facing a problem in reproducing the `balanced_accuracy_score` function.
Many resources converges on the equation of balanced accuracy as we can see in the link https://www.statology.org/balanced-accuracy-python-sklearn/. ... | 27,350 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27349 | [
"Enhancement"
] | SimpleImputer fails for columns with pandas string type
### Describe the bug
The SimpleImputer class with strategy="most_frequent" fails during fit when one of the columns of the input dataframe is of type string.
The error happens here https://github.com/scikit-learn/scikit-learn/blob/d8e131c1640f13954b2dd5f0cc... | 27,349 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27347 | [
"RFC"
] | RFC feature subsampling for tree based models
### Background
Currently, our (mostly tree-based) models supporting feature subsampling via `max_features` are:
- `DecisionTreeClassifier`, `DecisionTreeRegressor`
- `ExtraTreeClassifier`, `ExtraTreeRegressor`
- `BaggingClassifier`, `BaggingRegressor`
- `ExtraTreesCl... | 27,347 |
https://github.com/scikit-learn/scikit-learn/issues/27343 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.pylatest_pip_openblas_pandas ⚠️
**CI failed on [Linux.pylatest_pip_openblas_pandas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58914&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Sep 12, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
## ... | 27,343 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27342 | [
"Enhancement"
] | ENH Add `pos_label` parameter to `TargetEncoder`
### Describe the workflow you want to enable
Add a `pos_label` parameter to `TargetEncoder` to enable the user to specify which label should be the positive class when the target is binary.
### Describe your proposed solution
Add a `pos_label` parameter that is passe... | 27,342 |
https://github.com/scikit-learn/scikit-learn/issues/27340 | [
"Build / CI"
] | A welcome bot
Shall we add a welcome bot with a nice and pleasant message as:
https://github.com/scikit-learn/blog/pull/170
It gave me a cheesy feel-good moment, and I like these.
More seriously, I think t... | 27,340 |
https://github.com/scikit-learn/scikit-learn/issues/27340 | [
"Build / CI"
] | A welcome bot
Shall we add a welcome bot with a nice and pleasant message as:
https://github.com/scikit-learn/blog/pull/170
It gave me a cheesy feel-good moment, and I like these.
More seriously, I think t... | 27,340 |
https://github.com/scikit-learn/scikit-learn/issues/27340 | [
"Build / CI"
] | A welcome bot
Shall we add a welcome bot with a nice and pleasant message as:
https://github.com/scikit-learn/blog/pull/170
It gave me a cheesy feel-good moment, and I like these.
More seriously, I think t... | 27,340 |
https://github.com/scikit-learn/scikit-learn/issues/27340 | [
"Build / CI"
] | A welcome bot
Shall we add a welcome bot with a nice and pleasant message as:
https://github.com/scikit-learn/blog/pull/170
It gave me a cheesy feel-good moment, and I like these.
More seriously, I think t... | 27,340 |
https://github.com/scikit-learn/scikit-learn/issues/27340 | [
"Build / CI"
] | A welcome bot
Shall we add a welcome bot with a nice and pleasant message as:
https://github.com/scikit-learn/blog/pull/170
It gave me a cheesy feel-good moment, and I like these.
More seriously, I think t... | 27,340 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27339 | [
"help wanted",
"RFC"
] | RFC should the scikit-learn metrics return a Python scalar or a NumPy scalar?
While working on the representation imposed by NEP51, I found out that we recently made the `accuracy_score` to return a Python scalar while, up-to-now, other metric are returning NumPy scalar.
This change was made due to the array API wo... | 27,339 |
https://github.com/scikit-learn/scikit-learn/issues/27338 | [
"New Feature"
] | Feature Request: Out-of-Vocabulary (OOV) Token Handling in CountVectorizer
### Describe the workflow you want to enable
Users of CountVectorizer frequently encounter situations where, during the transformation of test data or new unseen data, there are words that the vectorizer hasn't seen during the training (fit) p... | 27,338 |
https://github.com/scikit-learn/scikit-learn/issues/27338 | [
"New Feature"
] | Feature Request: Out-of-Vocabulary (OOV) Token Handling in CountVectorizer
### Describe the workflow you want to enable
Users of CountVectorizer frequently encounter situations where, during the transformation of test data or new unseen data, there are words that the vectorizer hasn't seen during the training (fit) p... | 27,338 |
https://github.com/scikit-learn/scikit-learn/issues/27338 | [
"New Feature"
] | Feature Request: Out-of-Vocabulary (OOV) Token Handling in CountVectorizer
### Describe the workflow you want to enable
Users of CountVectorizer frequently encounter situations where, during the transformation of test data or new unseen data, there are words that the vectorizer hasn't seen during the training (fit) p... | 27,338 |
https://github.com/scikit-learn/scikit-learn/issues/27338 | [
"New Feature"
] | Feature Request: Out-of-Vocabulary (OOV) Token Handling in CountVectorizer
### Describe the workflow you want to enable
Users of CountVectorizer frequently encounter situations where, during the transformation of test data or new unseen data, there are words that the vectorizer hasn't seen during the training (fit) p... | 27,338 |
https://github.com/scikit-learn/scikit-learn/issues/27338 | [
"New Feature"
] | Feature Request: Out-of-Vocabulary (OOV) Token Handling in CountVectorizer
### Describe the workflow you want to enable
Users of CountVectorizer frequently encounter situations where, during the transformation of test data or new unseen data, there are words that the vectorizer hasn't seen during the training (fit) p... | 27,338 |
https://github.com/scikit-learn/scikit-learn/issues/27329 | [
"Needs Triage"
] | Convergence Warning message!!!
The optimization algorithm is not converging to a solution within the specified number of iterations.
Any Solution?
COMMENT:
Can you please include the full warning message you get and ideally a minimal reproducer?
https://scikit-learn.org/dev/developers/minimal_reproducer.html
I... | 27,329 |
https://github.com/scikit-learn/scikit-learn/issues/27329 | [
"Needs Triage"
] | Convergence Warning message!!!
The optimization algorithm is not converging to a solution within the specified number of iterations.
Any Solution?
COMMENT:
If none of the above works, please feel free to open a new issue with more details (at least the warning message, the code to trigger the problem and ideally a f... | 27,329 |
https://github.com/scikit-learn/scikit-learn/issues/27329 | [
"Needs Triage"
] | Convergence Warning message!!!
The optimization algorithm is not converging to a solution within the specified number of iterations.
Any Solution?
COMMENT:
Thank You!!! | 27,329 |
https://github.com/scikit-learn/scikit-learn/issues/27322 | [
"Bug"
] | 1 threads instead of multi-threading
### Describe the bug
Hello, I have a question regarding the following code: why is it running with only one thread instead of utilizing multiple threads? Thank you for your assistance.
X shape :(90, 16384) Y shape: (90, 261880)
R=RidgeCV(alphas=[0.1, 1, 100], gcv_mode='svd'... | 27,322 |
https://github.com/scikit-learn/scikit-learn/issues/27322 | [
"Bug"
] | 1 threads instead of multi-threading
### Describe the bug
Hello, I have a question regarding the following code: why is it running with only one thread instead of utilizing multiple threads? Thank you for your assistance.
X shape :(90, 16384) Y shape: (90, 261880)
R=RidgeCV(alphas=[0.1, 1, 100], gcv_mode='svd'... | 27,322 |
https://github.com/scikit-learn/scikit-learn/issues/27322 | [
"Bug"
] | 1 threads instead of multi-threading
### Describe the bug
Hello, I have a question regarding the following code: why is it running with only one thread instead of utilizing multiple threads? Thank you for your assistance.
X shape :(90, 16384) Y shape: (90, 261880)
R=RidgeCV(alphas=[0.1, 1, 100], gcv_mode='svd'... | 27,322 |
https://github.com/scikit-learn/scikit-learn/issues/27316 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58769&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Sep 08, 2023)
- test_pairwise_distances_argkmin[52-float32-parallel_on_X-braycurtis-1000000... | 27,316 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27313 | [
"Enhancement"
] | Implementation of Order Recursive Matching Pursuit
### Describe the workflow you want to enable
The sparse linear regression problem is the NP-hard problem of performing ordinary L² linear regression with the catch that at most a fixed number of the resulting coefficients can be non-zero (or the variation in which ... | 27,313 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27307 | [
"Documentation"
] | I can not achieve inplace scaling by using sklearn.preprocessing.minmax_scale
### Describe the bug
## By setting the copy=False, ndarray data has not changed unexpectedly
### Steps/Code to Reproduce
```pytho... | 27,307 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
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