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roc_auc_weighted metric addition (#827)

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* Pending changes exported from your codespace

* Update flaml/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update website/docs/Examples/Integrate - Scikit-learn Pipeline.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* added documentation for new metric

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* minor notebook changes

* Update Integrate - Scikit-learn Pipeline.md

* Update notebook/automl_classification.ipynb

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update integrate_azureml.ipynb

Co-authored-by: Chi Wang <wang.chi@microsoft.com>
This commit is contained in:
Shreyas
2022-12-03 08:57:32 +05:30
committed by GitHub
parent d213ae8f39
commit 3b3b0bfa8e
8 changed files with 111 additions and 26 deletions
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28
test/automl/test_multiclass.py
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@@ -318,6 +318,34 @@ class TestMultiClass(unittest.TestCase):
X_train, y_train = load_iris(return_X_y=True)
automl_experiment.fit(X_train=X_train, y_train=y_train, **automl_settings)
def test_roc_auc_ovr_weighted(self):
automl_experiment = AutoML()
automl_settings = {
"time_budget": 1,
"metric": "roc_auc_ovr_weighted",
"task": "classification",
"log_file_name": "test/roc_auc_weighted.log",
"log_training_metric": True,
"n_jobs": 1,
"model_history": True,
}
X_train, y_train = load_iris(return_X_y=True)
automl_experiment.fit(X_train=X_train, y_train=y_train, **automl_settings)
def test_roc_auc_ovo_weighted(self):
automl_experiment = AutoML()
automl_settings = {
"time_budget": 1,
"metric": "roc_auc_ovo_weighted",
"task": "classification",
"log_file_name": "test/roc_auc_weighted.log",
"log_training_metric": True,
"n_jobs": 1,
"model_history": True,
}
X_train, y_train = load_iris(return_X_y=True)
automl_experiment.fit(X_train=X_train, y_train=y_train, **automl_settings)
def test_sparse_matrix_classification(self):
automl_experiment = AutoML()
automl_settings = {