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Additional fixes to PR 777 #967

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Merged
PGijsbers merged 9 commits into from
Oct 29, 2020
Merged

Additional fixes to PR 777 #967

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0fb6230
Initial changes
Neeratyoy Oct 23, 2020
8fdde8a
Deleting TODO that will addressed by #968
Neeratyoy Oct 23, 2020
e6e4bbd
[skip ci] removing redundant imports
Neeratyoy Oct 23, 2020
b6b9f49
[skip ci] Simplifying flow to generate prediction probablities
Neeratyoy Oct 26, 2020
395985f
Triggering unit tests
Neeratyoy Oct 26, 2020
06c2e6a
Fixing mypy and flake issues
Neeratyoy Oct 26, 2020
d43cd1d
[skip ci] Replacing HistGradientBoostingClassifier
Neeratyoy Oct 27, 2020
2df584f
Simplifying examples
Neeratyoy Oct 27, 2020
534e43e
Minor typo fix
Neeratyoy Oct 27, 2020
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Initial changes
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@Neeratyoy
Neeratyoy committed Oct 23, 2020
commit 0fb62302c35bf30c5016b5e0ad7d6cc8393fad9b
2 changes: 1 addition & 1 deletion examples/30_extended/create_upload_tutorial.py
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Expand Up @@ -100,7 +100,7 @@
# The attribute that represents the row-id column, if present in the
# dataset.
row_id_attribute=None,
# Attribute or list of attributes that should be excluded in modelling, such as
# Attribute or list of attributes that should be excluded in modelling, such as
# identifiers and indexes. E.g. "feat1" or ["feat1","feat2"]
ignore_attribute=None,
# How to cite the paper.
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3 changes: 1 addition & 2 deletions examples/30_extended/study_tutorial.py
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Expand Up @@ -16,7 +16,6 @@
import uuid

import numpy as np
import sklearn.tree
from sklearn.pipeline import make_pipeline, Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.impute import SimpleImputer
Expand Down Expand Up @@ -71,7 +70,7 @@
)
print(evaluations.head())

###########################################################from openml.testing import cat, cont#################
############################################################################
# Uploading studies
# =================
#
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5 changes: 3 additions & 2 deletions openml/extensions/sklearn/extension.py
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Expand Up @@ -1581,8 +1581,8 @@ def _run_model_on_fold(
-------
pred_y : np.ndarray
Predictions on the training/test set, depending on the task type.
For supervised tasks, predicitons are on the test set.
For unsupervised tasks, predicitons are on the training set.
For supervised tasks, predictions are on the test set.
For unsupervised tasks, predictions are on the training set.
proba_y : pd.DataFrame
Predicted probabilities for the test set.
None, if task is not Classification or Learning Curve prediction.
Expand Down Expand Up @@ -1759,6 +1759,7 @@ def _prediction_to_probabilities(y: np.ndarray, model_classes: List[Any]) -> pd.
# adding missing columns with 0 probability
if col not in model_classes:
proba_y[col] = 0
# We re-order the columns to move possibly added missing columns into place.
proba_y = proba_y[task.class_labels]
else:
raise ValueError("The task has no class labels")
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