html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k | embedding listlengths 768 768 |
|---|---|---|---|---|
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
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 | [
-0.024049928411841393,
0.06095851957798004,
0.035001643002033234,
-0.02311539463698864,
0.05334573984146118,
0.03988242894411087,
0.08239445090293884,
-0.0035029833670705557,
0.004978629294782877,
0.004015618935227394,
-0.033846985548734665,
0.06425856053829193,
0.0311697106808424,
0.06895... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25889 | [
"New Feature",
"module:pipeline"
] | FeatureUnion: Add verbose_feature_names_out parameter
### Describe the workflow you want to enable
`ColumnTransformer` has the option to specify whether or not to "prefix all feature names with the name of the transformer that generated that feature" using the `verbose_feature_names_out` parameter.
`FeatureUnion` ... | 25,889 | [
0.02191835455596447,
0.04849579185247421,
0.016155188903212547,
-0.037469398230314255,
0.03835903853178024,
0.03079088404774666,
0.06382380425930023,
-0.02239721082150936,
-0.04474582150578499,
-0.0023781689815223217,
0.017327921465039253,
0.03388424962759018,
-0.011836103163659573,
0.0765... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25888 | [
"Performance",
"cython",
"Meta-issue"
] | PERF `PairwiseDistancesReductions` subsequent work
`PairwiseDistancesReductions` have been introduced as a hierarchy of Cython classes to implement back-ends of some scikit-learn algorithms.
Initial work was listed in #22587.
:bulb: See [this presentation](https://docs.google.com/presentation/d/1RwX_P9lnsb9_YRZ0... | 25,888 | [
-0.0191729087382555,
0.0030274377204477787,
0.020122187212109566,
0.05014197155833244,
-0.04992770403623581,
0.0029531805776059628,
0.07141869515180588,
0.012887690216302872,
0.017557799816131592,
-0.0423978790640831,
0.004888430703431368,
0.03149869665503502,
0.005422086920589209,
-0.0470... |
https://github.com/scikit-learn/scikit-learn/issues/25883 | [
"Bug",
"Needs Triage"
] | IterativeImputer - keep_empty_features parameter contains a bug
### Describe the bug
By making the "keep_empty_features" parameter to be True, then I found the behavior of the iterative imputation is the same as the simple imputation, which is a bug. By looking at the code, I found line 633 of _iterative.py "mask_m... | 25,883 | [
0.022330954670906067,
-0.012758376076817513,
0.029369954019784927,
-0.02398790791630745,
0.03071151301264763,
-0.004756935406476259,
0.06374732404947281,
0.018346823751926422,
0.040594812482595444,
0.022248711436986923,
0.06284761428833008,
0.006602552719414234,
0.041806742548942566,
-0.00... |
https://github.com/scikit-learn/scikit-learn/issues/25883 | [
"Bug",
"Needs Triage"
] | IterativeImputer - keep_empty_features parameter contains a bug
### Describe the bug
By making the "keep_empty_features" parameter to be True, then I found the behavior of the iterative imputation is the same as the simple imputation, which is a bug. By looking at the code, I found line 633 of _iterative.py "mask_m... | 25,883 | [
0.022330954670906067,
-0.012758376076817513,
0.029369954019784927,
-0.02398790791630745,
0.03071151301264763,
-0.004756935406476259,
0.06374732404947281,
0.018346823751926422,
0.040594812482595444,
0.022248711436986923,
0.06284761428833008,
0.006602552719414234,
0.041806742548942566,
-0.00... |
https://github.com/scikit-learn/scikit-learn/issues/25883 | [
"Bug",
"Needs Triage"
] | IterativeImputer - keep_empty_features parameter contains a bug
### Describe the bug
By making the "keep_empty_features" parameter to be True, then I found the behavior of the iterative imputation is the same as the simple imputation, which is a bug. By looking at the code, I found line 633 of _iterative.py "mask_m... | 25,883 | [
0.022330954670906067,
-0.012758376076817513,
0.029369954019784927,
-0.02398790791630745,
0.03071151301264763,
-0.004756935406476259,
0.06374732404947281,
0.018346823751926422,
0.040594812482595444,
0.022248711436986923,
0.06284761428833008,
0.006602552719414234,
0.041806742548942566,
-0.00... |
https://github.com/scikit-learn/scikit-learn/issues/25881 | [
"Needs Triage"
] | Appears that the checking of deprecated attributes in turn causing issues
##########
environment info
--------------
Microsoft Windows [Version 10.0.19045.2604]
(c) Microsoft Corporation. All rights r... | 25,881 | [
-0.005143265705555677,
0.003540115198120475,
0.007557221222668886,
-0.04809016361832619,
0.09940239042043686,
0.02066810056567192,
0.044449348002672195,
0.0368247851729393,
0.03441973775625229,
-0.011795216239988804,
0.04448423534631729,
0.03159286081790924,
0.006370811257511377,
0.0136984... |
https://github.com/scikit-learn/scikit-learn/issues/25881 | [
"Needs Triage"
] | Appears that the checking of deprecated attributes in turn causing issues
##########
environment info
--------------
Microsoft Windows [Version 10.0.19045.2604]
(c) Microsoft Corporation. All rights r... | 25,881 | [
-0.0009204010711982846,
0.008339117281138897,
0.007967819459736347,
-0.05351538583636284,
0.09899557381868362,
0.024484658613801003,
0.03649148717522621,
0.03566831722855568,
0.029070086777210236,
-0.016205232590436935,
0.040558915585279465,
0.030179237946867943,
-0.0025502147618681192,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/25881 | [
"Needs Triage"
] | Appears that the checking of deprecated attributes in turn causing issues
##########
environment info
--------------
Microsoft Windows [Version 10.0.19045.2604]
(c) Microsoft Corporation. All rights r... | 25,881 | [
0.032231081277132034,
0.02030627615749836,
0.017595672979950905,
-0.044495563954114914,
0.06827890872955322,
0.031813982874155045,
0.02661360800266266,
0.030229361727833748,
0.04258916527032852,
-0.032470472157001495,
0.06050858646631241,
0.007339551579207182,
-0.0017749795224517584,
0.001... |
https://github.com/scikit-learn/scikit-learn/issues/25881 | [
"Needs Triage"
] | Appears that the checking of deprecated attributes in turn causing issues
##########
environment info
--------------
Microsoft Windows [Version 10.0.19045.2604]
(c) Microsoft Corporation. All rights r... | 25,881 | [
0.0047125983983278275,
0.006314900703728199,
0.01511357445269823,
-0.05004777014255524,
0.09523818641901016,
0.029191477224230766,
0.035001832991838455,
0.04380917549133301,
0.030263155698776245,
-0.015160204842686653,
0.042226292192935944,
0.030109182000160217,
-0.0015972316032275558,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/25881 | [
"Needs Triage"
] | Appears that the checking of deprecated attributes in turn causing issues
##########
environment info
--------------
Microsoft Windows [Version 10.0.19045.2604]
(c) Microsoft Corporation. All rights r... | 25,881 | [
-0.0013624574057757854,
0.004101026337593794,
0.005349737126380205,
-0.05021999031305313,
0.10070644319057465,
0.02296648733317852,
0.04138556867837906,
0.0376824326813221,
0.030609704554080963,
-0.020651938393712044,
0.035773470997810364,
0.03285374864935875,
0.0042451852932572365,
0.0112... |
https://github.com/scikit-learn/scikit-learn/issues/25874 | [
"New Feature",
"Needs Decision - Include Feature"
] | make_classification: allow shuffling of samples only
### Describe the workflow you want to enable
At present, `make_classification` allows shuffling both the samples and the features. I would like to create a sample dataset with some categorical features, and I can do that by thresholding some of the features. I ha... | 25,874 | [
-0.017862770706415176,
0.037100907415151596,
0.011397832073271275,
-0.019145311787724495,
0.011920174583792686,
0.012240638956427574,
0.059676941484212875,
-0.00367364170961082,
0.023500956594944,
-0.06337080150842667,
0.039995890110731125,
0.03954117000102997,
-0.035726990550756454,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/25874 | [
"New Feature",
"Needs Decision - Include Feature"
] | make_classification: allow shuffling of samples only
### Describe the workflow you want to enable
At present, `make_classification` allows shuffling both the samples and the features. I would like to create a sample dataset with some categorical features, and I can do that by thresholding some of the features. I ha... | 25,874 | [
-0.03022855706512928,
0.03575941547751427,
-0.004313258919864893,
-0.008216348476707935,
0.011591828428208828,
0.015234975144267082,
0.05102214589715004,
-0.009002773091197014,
0.02111019194126129,
-0.059124454855918884,
0.04970397427678108,
0.0383417047560215,
-0.04049563407897949,
0.0583... |
https://github.com/scikit-learn/scikit-learn/issues/25874 | [
"New Feature",
"Needs Decision - Include Feature"
] | make_classification: allow shuffling of samples only
### Describe the workflow you want to enable
At present, `make_classification` allows shuffling both the samples and the features. I would like to create a sample dataset with some categorical features, and I can do that by thresholding some of the features. I ha... | 25,874 | [
-0.03784903138875961,
0.04035446047782898,
-0.01743980497121811,
-0.008044447749853134,
-0.006659935228526592,
0.006751560606062412,
0.050720278173685074,
-0.005997354164719582,
0.00282851280644536,
-0.057136524468660355,
0.04960478097200394,
0.015547760762274265,
-0.05338145047426224,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/25859 | [
"New Feature",
"API",
"Needs Decision"
] | How to early stop in GradientBoostingClassifer?
How to track the model performance on an eval set that is provided from outside and early stop the tree building based upon the result?
Currently there is the option of ```validation_fraction``` along with ```n_iter_no_change``` available in the implementation
The is... | 25,859 | [
-0.05331046134233475,
0.04481523111462593,
0.04332380369305611,
-0.04014977812767029,
0.04379969462752342,
-0.02182386815547943,
-0.016833484172821045,
0.0010513759916648269,
-0.056716881692409515,
0.013052474707365036,
0.044328536838293076,
-0.016924424096941948,
-0.02734566479921341,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25856 | [
"New Feature",
"Needs Decision - Include Feature"
] | Sampling uncertainty on precision-recall and ROC curves
### Describe the workflow you want to enable
We would like to add the possibility to plot sampling uncertainty on precision-recall and ROC curves.
### Describe your proposed solution
We (@mbaak, @RUrlus, @ilanfri and I) published a paper in [AISTAT 202... | 25,856 | [
-0.03139527887105942,
-0.006420718505978584,
0.0202446598559618,
0.010100175626575947,
-0.013829560950398445,
-0.027906181290745735,
-0.02502017840743065,
-0.01947672851383686,
-0.006580352317541838,
0.017551682889461517,
-0.006669738329946995,
0.0019722706638276577,
0.0011102448916062713,
... |
https://github.com/scikit-learn/scikit-learn/issues/25855 | [
"New Feature",
"wontfix"
] | Add sample weights to Nearest Neighbors classifiers
### Describe the workflow you want to enable
Both `KNeighborsClassifier` and `RadiusNeighborsClassifier` support providing weights, determined as a function of the distances of the neighboring samples. However, it is not possible to provide `sample_weight`, usually ... | 25,855 | [
0.000014683020708616823,
0.050681110471487045,
0.013288670219480991,
-0.018365509808063507,
-0.018296530470252037,
-0.02704637497663498,
0.018397079780697823,
0.029362842440605164,
0.041825760155916214,
0.011425442062318325,
-0.01228918507695198,
-0.0028105091769248247,
-0.05078807473182678,... |
https://github.com/scikit-learn/scikit-learn/issues/25855 | [
"New Feature",
"wontfix"
] | Add sample weights to Nearest Neighbors classifiers
### Describe the workflow you want to enable
Both `KNeighborsClassifier` and `RadiusNeighborsClassifier` support providing weights, determined as a function of the distances of the neighboring samples. However, it is not possible to provide `sample_weight`, usually ... | 25,855 | [
0.000014683020708616823,
0.050681110471487045,
0.013288670219480991,
-0.018365509808063507,
-0.018296530470252037,
-0.02704637497663498,
0.018397079780697823,
0.029362842440605164,
0.041825760155916214,
0.011425442062318325,
-0.01228918507695198,
-0.0028105091769248247,
-0.05078807473182678,... |
https://github.com/scikit-learn/scikit-learn/issues/25855 | [
"New Feature",
"wontfix"
] | Add sample weights to Nearest Neighbors classifiers
### Describe the workflow you want to enable
Both `KNeighborsClassifier` and `RadiusNeighborsClassifier` support providing weights, determined as a function of the distances of the neighboring samples. However, it is not possible to provide `sample_weight`, usually ... | 25,855 | [
0.000014683020708616823,
0.050681110471487045,
0.013288670219480991,
-0.018365509808063507,
-0.018296530470252037,
-0.02704637497663498,
0.018397079780697823,
0.029362842440605164,
0.041825760155916214,
0.011425442062318325,
-0.01228918507695198,
-0.0028105091769248247,
-0.05078807473182678,... |
https://github.com/scikit-learn/scikit-learn/issues/25855 | [
"New Feature",
"wontfix"
] | Add sample weights to Nearest Neighbors classifiers
### Describe the workflow you want to enable
Both `KNeighborsClassifier` and `RadiusNeighborsClassifier` support providing weights, determined as a function of the distances of the neighboring samples. However, it is not possible to provide `sample_weight`, usually ... | 25,855 | [
0.000014683020708616823,
0.050681110471487045,
0.013288670219480991,
-0.018365509808063507,
-0.018296530470252037,
-0.02704637497663498,
0.018397079780697823,
0.029362842440605164,
0.041825760155916214,
0.011425442062318325,
-0.01228918507695198,
-0.0028105091769248247,
-0.05078807473182678,... |
https://github.com/scikit-learn/scikit-learn/issues/25855 | [
"New Feature",
"wontfix"
] | Add sample weights to Nearest Neighbors classifiers
### Describe the workflow you want to enable
Both `KNeighborsClassifier` and `RadiusNeighborsClassifier` support providing weights, determined as a function of the distances of the neighboring samples. However, it is not possible to provide `sample_weight`, usually ... | 25,855 | [
0.000014683020708616823,
0.050681110471487045,
0.013288670219480991,
-0.018365509808063507,
-0.018296530470252037,
-0.02704637497663498,
0.018397079780697823,
0.029362842440605164,
0.041825760155916214,
0.011425442062318325,
-0.01228918507695198,
-0.0028105091769248247,
-0.05078807473182678,... |
https://github.com/scikit-learn/scikit-learn/issues/25854 | [
"Bug",
"New Feature"
] | `KNeighborsClassifier` with Default Label
### Describe the workflow you want to enable
In `KNeighborsClassifier`, for a user-provided callable `weights` parameter, it would be nice to allow for a situation with no winner. Say I want to give a weight of `0.0` to samples that are "too far away". Then, there can be a si... | 25,854 | [
0.002130816923454404,
0.022995557636022568,
0.020351596176624298,
-0.004498166032135487,
0.00378322321921587,
-0.040567729622125626,
-0.000839653133880347,
0.014995988458395004,
0.02122759260237217,
-0.02680840902030468,
0.04311472922563553,
0.022262025624513626,
-0.08685949444770813,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/25846 | [
"Bug",
"Needs Triage"
] | cross validation with Sklearn pipeline using custom data preprocessing
### Describe the bug
I am using this custom sklearn pipeline:
```python
import numpy as np
import pandas as pd
from sklearn.model_selection import cross_validate
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline imp... | 25,846 | [
-0.04789543151855469,
0.0162039864808321,
0.031037883833050728,
-0.030924247577786446,
0.10256674885749817,
-0.015773678198456764,
0.02253146842122078,
0.005489009898155928,
0.02426481433212757,
0.007062960881739855,
0.029736213386058807,
0.042286086827516556,
0.018673796206712723,
0.09217... |
https://github.com/scikit-learn/scikit-learn/issues/25846 | [
"Bug",
"Needs Triage"
] | cross validation with Sklearn pipeline using custom data preprocessing
### Describe the bug
I am using this custom sklearn pipeline:
```python
import numpy as np
import pandas as pd
from sklearn.model_selection import cross_validate
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline imp... | 25,846 | [
-0.04789543151855469,
0.0162039864808321,
0.031037883833050728,
-0.030924247577786446,
0.10256674885749817,
-0.015773678198456764,
0.02253146842122078,
0.005489009898155928,
0.02426481433212757,
0.007062960881739855,
0.029736213386058807,
0.042286086827516556,
0.018673796206712723,
0.09217... |
https://github.com/scikit-learn/scikit-learn/issues/25846 | [
"Bug",
"Needs Triage"
] | cross validation with Sklearn pipeline using custom data preprocessing
### Describe the bug
I am using this custom sklearn pipeline:
```python
import numpy as np
import pandas as pd
from sklearn.model_selection import cross_validate
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline imp... | 25,846 | [
-0.04789543151855469,
0.0162039864808321,
0.031037883833050728,
-0.030924247577786446,
0.10256674885749817,
-0.015773678198456764,
0.02253146842122078,
0.005489009898155928,
0.02426481433212757,
0.007062960881739855,
0.029736213386058807,
0.042286086827516556,
0.018673796206712723,
0.09217... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
https://github.com/scikit-learn/scikit-learn/issues/25844 | [
"Bug",
"good first issue"
] | X does not have valid feature names, but IsolationForest was fitted with feature names
### Describe the bug
If you fit an `IsolationForest` using a `pd.DataFrame` it generates a warning
``` python
X does not have valid feature names, but IsolationForest was fitted with feature names
```
This only seems to o... | 25,844 | [
0.04302222654223442,
-0.004146065097302198,
0.03038197010755539,
-0.011840900406241417,
0.060698214918375015,
-0.00468160305172205,
0.0713244304060936,
-0.009555676952004433,
0.057546455413103104,
0.028425002470612526,
0.03117707185447216,
-0.011835243552923203,
0.023097118362784386,
0.056... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.