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Merge branch 'master' into master
2 parents 57463cf + 5c81e31 commit e8af236

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5 files changed

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.github/workflows/benchmarking-files/benchmarks/classification.yaml

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# binary, highly imbalanced, 2109 instances, 22 features, 2 labels
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- name: kc1
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openml_task_id: 3917
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openml_task_id: 3917
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---
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10fold10min:
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folds: 10
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max_runtime_seconds: 600
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max_runtime_seconds: 600

.github/workflows/benchmarking-files/regressions-util.py

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CLASSIFICATION_METRICS = ['acc', 'auc', 'balacc', 'logloss']
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REGRESSION_METRICS = ['mae', 'r2', 'rmse']
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METRICS = CLASSIFICATION_METRICS + REGRESSION_METRICS
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def _get_mean_results_across_folds(df) -> pd.DataFrame:
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""" Returns a dataframe with the task, id, metric and the mean values
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across folds
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# Using branch and https
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version = branch
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repo = f'https://github.com/{username}/auto-sklearn.git'
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# Create the framework file
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lines = '\n'.join([
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f"---",
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Comparisons here is the difference between (targeted - baseline)
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Returns them in that specific order
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"""
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# Load in data and get the means across folds
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df_baseline_classification = pd.read_csv(baseline_csv_classification)
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df_baseline_regression = pd.read_csv(baseline_csv_regression)
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df_targeted_classification = pd.read_csv(targeted_csv_classification)
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df_targeted_regression = pd.read_csv(targeted_csv_regression)
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df_targeted = pd.concat([df_targeted_classification, df_targeted_regression])
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df_targeted_means = _get_mean_results_across_folds(df_targeted)
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# Find the set intersection of tasks they have in common
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if args.generate_framework_def:
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assert args.owner and args.branch and args.commit and args.user_dir
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generate_framework_def(args.user_dir, args.owner, args.branch, args.commit)
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elif args.compare_results:

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