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/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25950 | [
"Bug",
"Needs Triage"
] | Lasso loss is (mathematically) invariant wrt simultaneous rotation of X and y, but the solver outcome is not
### Describe the bug
For any given set of coefficients and intercept, the Lasso loss is invariant with respect to replacing X and y with U@X and U@y, where U is any orthonormal matrix (proof see below). Howeve... | 25,950 |
https://github.com/scikit-learn/scikit-learn/issues/25946 | [
"Bug",
"Needs Triage"
] | Output redirection is broken
### Describe the bug
I'm trying to redirect output from a script that uses Scikit-Learn to a file, as follows:
`python myscript.py > mylog.log 2>&1`
This should redirect both stdout and stderr to _mylog.log_. Most of my code uses logging statements which, as expected, are written to... | 25,946 |
https://github.com/scikit-learn/scikit-learn/issues/25946 | [
"Bug",
"Needs Triage"
] | Output redirection is broken
### Describe the bug
I'm trying to redirect output from a script that uses Scikit-Learn to a file, as follows:
`python myscript.py > mylog.log 2>&1`
This should redirect both stdout and stderr to _mylog.log_. Most of my code uses logging statements which, as expected, are written to... | 25,946 |
https://github.com/scikit-learn/scikit-learn/issues/25946 | [
"Bug",
"Needs Triage"
] | Output redirection is broken
### Describe the bug
I'm trying to redirect output from a script that uses Scikit-Learn to a file, as follows:
`python myscript.py > mylog.log 2>&1`
This should redirect both stdout and stderr to _mylog.log_. Most of my code uses logging statements which, as expected, are written to... | 25,946 |
https://github.com/scikit-learn/scikit-learn/issues/25946 | [
"Bug",
"Needs Triage"
] | Output redirection is broken
### Describe the bug
I'm trying to redirect output from a script that uses Scikit-Learn to a file, as follows:
`python myscript.py > mylog.log 2>&1`
This should redirect both stdout and stderr to _mylog.log_. Most of my code uses logging statements which, as expected, are written to... | 25,946 |
https://github.com/scikit-learn/scikit-learn/issues/25944 | [
"Bug"
] | Polynomial features min degree and max degree not working properly
### Describe the bug
I'm trying to use the PolynomialFeatures to generate 2nd order terms and exclude linear ones. According to the documentation, this should look like this:
`poly = PolynomialFeatures(degree=(2,2),interaction_only=True)`
But ... | 25,944 |
https://github.com/scikit-learn/scikit-learn/issues/25944 | [
"Bug"
] | Polynomial features min degree and max degree not working properly
### Describe the bug
I'm trying to use the PolynomialFeatures to generate 2nd order terms and exclude linear ones. According to the documentation, this should look like this:
`poly = PolynomialFeatures(degree=(2,2),interaction_only=True)`
But ... | 25,944 |
https://github.com/scikit-learn/scikit-learn/issues/25937 | [
"Needs Triage"
] | Unstable sklearn/svm/tests/test_bounds.py::test_newrand_set_seed
On my local laptop I often observe a random failure for `test_newrand_set_seed`.
I am running macos m1 with Python 3.11 from conda-forge. scikit-learn has been built with the clang compilers from conda-forge.
Here is a typical run with 10 repetitio... | 25,937 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25935 | [
"Bug"
] | BaggingClassifier throws ValueError: WRITEBACKIFCOPY base is read-only
### Describe the bug
When I use the bagging-classifier in conjunction with LinearSVC it throws `ValueError: WRITEBACKIFCOPY base is read-only` when `n_jobs!=1`.
Changing `n_jobs` to 1 removes the error
### Steps/Code to Reproduce
The i... | 25,935 |
https://github.com/scikit-learn/scikit-learn/issues/25933 | [
"Bug"
] | Potentially unsafe cast in sklearn.utils.multiclass.type_of_target
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25835
<div type='discussions-op-text'>
<sup>Originally posted by **thomasryck** March 13, 2023</sup>
Hi
I was using the method type_of_target from the multiclass file.
... | 25,933 |
https://github.com/scikit-learn/scikit-learn/issues/25933 | [
"Bug"
] | Potentially unsafe cast in sklearn.utils.multiclass.type_of_target
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25835
<div type='discussions-op-text'>
<sup>Originally posted by **thomasryck** March 13, 2023</sup>
Hi
I was using the method type_of_target from the multiclass file.
... | 25,933 |
https://github.com/scikit-learn/scikit-learn/issues/25933 | [
"Bug"
] | Potentially unsafe cast in sklearn.utils.multiclass.type_of_target
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25835
<div type='discussions-op-text'>
<sup>Originally posted by **thomasryck** March 13, 2023</sup>
Hi
I was using the method type_of_target from the multiclass file.
... | 25,933 |
https://github.com/scikit-learn/scikit-learn/issues/25933 | [
"Bug"
] | Potentially unsafe cast in sklearn.utils.multiclass.type_of_target
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25835
<div type='discussions-op-text'>
<sup>Originally posted by **thomasryck** March 13, 2023</sup>
Hi
I was using the method type_of_target from the multiclass file.
... | 25,933 |
https://github.com/scikit-learn/scikit-learn/issues/25933 | [
"Bug"
] | Potentially unsafe cast in sklearn.utils.multiclass.type_of_target
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25835
<div type='discussions-op-text'>
<sup>Originally posted by **thomasryck** March 13, 2023</sup>
Hi
I was using the method type_of_target from the multiclass file.
... | 25,933 |
https://github.com/scikit-learn/scikit-learn/issues/25932 | [
"Bug",
"Needs Info"
] | Random forest classifier probability is negative
### Describe the bug
Random forest classifier probability is negative value
### Steps/Code to Reproduce
```py
import numpy as np
clf = RandomForestClassifier(n_estimators=500, max_depth=50, random_state=0, min_samples_split = 10, min_samples_leaf = 10)
clf... | 25,932 |
https://github.com/scikit-learn/scikit-learn/issues/25932 | [
"Bug",
"Needs Info"
] | Random forest classifier probability is negative
### Describe the bug
Random forest classifier probability is negative value
### Steps/Code to Reproduce
```py
import numpy as np
clf = RandomForestClassifier(n_estimators=500, max_depth=50, random_state=0, min_samples_split = 10, min_samples_leaf = 10)
clf... | 25,932 |
https://github.com/scikit-learn/scikit-learn/issues/25932 | [
"Bug",
"Needs Info"
] | Random forest classifier probability is negative
### Describe the bug
Random forest classifier probability is negative value
### Steps/Code to Reproduce
```py
import numpy as np
clf = RandomForestClassifier(n_estimators=500, max_depth=50, random_state=0, min_samples_split = 10, min_samples_leaf = 10)
clf... | 25,932 |
https://github.com/scikit-learn/scikit-learn/issues/25932 | [
"Bug",
"Needs Info"
] | Random forest classifier probability is negative
### Describe the bug
Random forest classifier probability is negative value
### Steps/Code to Reproduce
```py
import numpy as np
clf = RandomForestClassifier(n_estimators=500, max_depth=50, random_state=0, min_samples_split = 10, min_samples_leaf = 10)
clf... | 25,932 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25929 | [
"Enhancement"
] | Visual improvements for ROC and precision-recall plots
### Describe the workflow you want to enable
Hello,
I would like to suggest the following improvements:
- [x] (1) Add x and y axis limit: [0, 1], in sklearn axes currently start at ~-0.1 (#26366)
- [x] (2) Modify the plotting frame: either remove the top... | 25,929 |
https://github.com/scikit-learn/scikit-learn/issues/25923 | [
"Bug"
] | average_precision_score() and roc_auc_score() require a full list of arguments
### Describe the bug
These two functions, namely average_precision_score() and roc_auc_score() require a full list of arguments. Otherwise, it reports errors!
### Steps/Code to Reproduce
```
import numpy as np
from sklearn.metrics ... | 25,923 |
https://github.com/scikit-learn/scikit-learn/issues/25923 | [
"Bug"
] | average_precision_score() and roc_auc_score() require a full list of arguments
### Describe the bug
These two functions, namely average_precision_score() and roc_auc_score() require a full list of arguments. Otherwise, it reports errors!
### Steps/Code to Reproduce
```
import numpy as np
from sklearn.metrics ... | 25,923 |
https://github.com/scikit-learn/scikit-learn/issues/25922 | [
"New Feature",
"Needs Decision - Include Feature"
] | Make complex numbers check optional in `BaseEstimator._validate_and_set_fit_params`
### Describe the workflow you want to enable
I recently extended my library [PySR](https://github.com/MilesCranmer/PySR) to allow for complex `X` and `y` arrays. However, the function `BaseEstimator._validate_and_set_fit_params` has... | 25,922 |
https://github.com/scikit-learn/scikit-learn/issues/25922 | [
"New Feature",
"Needs Decision - Include Feature"
] | Make complex numbers check optional in `BaseEstimator._validate_and_set_fit_params`
### Describe the workflow you want to enable
I recently extended my library [PySR](https://github.com/MilesCranmer/PySR) to allow for complex `X` and `y` arrays. However, the function `BaseEstimator._validate_and_set_fit_params` has... | 25,922 |
https://github.com/scikit-learn/scikit-learn/issues/25922 | [
"New Feature",
"Needs Decision - Include Feature"
] | Make complex numbers check optional in `BaseEstimator._validate_and_set_fit_params`
### Describe the workflow you want to enable
I recently extended my library [PySR](https://github.com/MilesCranmer/PySR) to allow for complex `X` and `y` arrays. However, the function `BaseEstimator._validate_and_set_fit_params` has... | 25,922 |
https://github.com/scikit-learn/scikit-learn/issues/25922 | [
"New Feature",
"Needs Decision - Include Feature"
] | Make complex numbers check optional in `BaseEstimator._validate_and_set_fit_params`
### Describe the workflow you want to enable
I recently extended my library [PySR](https://github.com/MilesCranmer/PySR) to allow for complex `X` and `y` arrays. However, the function `BaseEstimator._validate_and_set_fit_params` has... | 25,922 |
https://github.com/scikit-learn/scikit-learn/issues/25922 | [
"New Feature",
"Needs Decision - Include Feature"
] | Make complex numbers check optional in `BaseEstimator._validate_and_set_fit_params`
### Describe the workflow you want to enable
I recently extended my library [PySR](https://github.com/MilesCranmer/PySR) to allow for complex `X` and `y` arrays. However, the function `BaseEstimator._validate_and_set_fit_params` has... | 25,922 |
https://github.com/scikit-learn/scikit-learn/issues/25908 | [
"Needs Triage"
] | make_classification: variances of informative, redundant and useless features differ significantly
In this part of the code for `make_classification`, the informative and redundant features are generated; here is the informative part:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440c... | 25,908 |
https://github.com/scikit-learn/scikit-learn/issues/25908 | [
"Needs Triage"
] | make_classification: variances of informative, redundant and useless features differ significantly
In this part of the code for `make_classification`, the informative and redundant features are generated; here is the informative part:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440c... | 25,908 |
https://github.com/scikit-learn/scikit-learn/issues/25908 | [
"Needs Triage"
] | make_classification: variances of informative, redundant and useless features differ significantly
In this part of the code for `make_classification`, the informative and redundant features are generated; here is the informative part:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440c... | 25,908 |
https://github.com/scikit-learn/scikit-learn/issues/25908 | [
"Needs Triage"
] | make_classification: variances of informative, redundant and useless features differ significantly
In this part of the code for `make_classification`, the informative and redundant features are generated; here is the informative part:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440c... | 25,908 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25906 | [
"Bug",
"module:linear_model"
] | Use sample_weight when validating LogisticRegressionCV
Metadata Routing https://github.com/scikit-learn/scikit-learn/pull/24027 will add much needed support for taking into account sample_weight when cross-validating. However, the current implementation of LogisticRegressionCV doesn't seem to be taking advantage of th... | 25,906 |
https://github.com/scikit-learn/scikit-learn/issues/25903 | [
"Needs Triage"
] | make_classification: repeated features are not chosen uniformly at random
I have just noticed that this piece of code in `make_classification` which selects features to repeat does not do so uniformly at random:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440ca9eb239/sklearn/dataset... | 25,903 |
https://github.com/scikit-learn/scikit-learn/issues/25903 | [
"Needs Triage"
] | make_classification: repeated features are not chosen uniformly at random
I have just noticed that this piece of code in `make_classification` which selects features to repeat does not do so uniformly at random:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440ca9eb239/sklearn/dataset... | 25,903 |
https://github.com/scikit-learn/scikit-learn/issues/25903 | [
"Needs Triage"
] | make_classification: repeated features are not chosen uniformly at random
I have just noticed that this piece of code in `make_classification` which selects features to repeat does not do so uniformly at random:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440ca9eb239/sklearn/dataset... | 25,903 |
https://github.com/scikit-learn/scikit-learn/issues/25903 | [
"Needs Triage"
] | make_classification: repeated features are not chosen uniformly at random
I have just noticed that this piece of code in `make_classification` which selects features to repeat does not do so uniformly at random:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440ca9eb239/sklearn/dataset... | 25,903 |
https://github.com/scikit-learn/scikit-learn/issues/25903 | [
"Needs Triage"
] | make_classification: repeated features are not chosen uniformly at random
I have just noticed that this piece of code in `make_classification` which selects features to repeat does not do so uniformly at random:
https://github.com/scikit-learn/scikit-learn/blob/9aaed498795f68e5956ea762fef9c440ca9eb239/sklearn/dataset... | 25,903 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
https://github.com/scikit-learn/scikit-learn/issues/25896 | [
"New Feature",
"RFC"
] | Support other dataframes like polars and pyarrow not just pandas
### Describe the workflow you want to enable
Currently, scikit-learn nowhere claims to support [pyarrow](https://arrow.apache.org/docs/python/) or [polars](https://www.pola.rs/). And indeed,
```python
import numpy as np
from sklearn.datasets import... | 25,896 |
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