ludwig-ai--ludwig
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229 行
8.2 KiB
Python
229 行
8.2 KiB
Python
# Copyright (c) 2023 Predibase, Inc., 2019 Uber Technologies, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""ludwig.visualize package — backward-compatible re-exports.
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All public and private symbols that were importable from ``ludwig.visualize``
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when it was a single module remain importable from this package.
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"""
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# ---------------------------------------------------------------------------
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# Private helpers / data-loading utilities
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# ---------------------------------------------------------------------------
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from ludwig.visualize._utils import (
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_convert_ground_truth,
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_CSV_SUFFIX,
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_encode_categorical_feature,
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_extract_ground_truth_values,
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_get_cols_from_predictions,
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_get_ground_truth_df,
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_load_training_stats,
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_PARQUET_SUFFIX,
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_PREDICTIONS_SUFFIX,
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_PROBABILITIES_SUFFIX,
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_validate_output_feature_name_from_test_stats,
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_validate_output_feature_name_from_train_stats,
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_vectorize_ground_truth,
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convert_to_list,
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generate_filename_template_path,
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load_data_for_viz,
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load_training_stats_for_viz,
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validate_conf_thresholds_and_probabilities_2d_3d,
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)
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# ---------------------------------------------------------------------------
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# CLI entry point + registry
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# ---------------------------------------------------------------------------
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from ludwig.visualize.cli import (
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cli,
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get_visualizations_registry,
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)
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# ---------------------------------------------------------------------------
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# Confusion matrix
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# ---------------------------------------------------------------------------
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from ludwig.visualize.confusion import (
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confusion_matrix,
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confusion_matrix_cli,
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)
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# ---------------------------------------------------------------------------
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# ROC, precision-recall, calibration curves
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# ---------------------------------------------------------------------------
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from ludwig.visualize.curves import (
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calibration_1_vs_all,
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calibration_1_vs_all_cli,
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calibration_multiclass,
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calibration_multiclass_cli,
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precision_recall_curves,
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precision_recall_curves_cli,
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precision_recall_curves_from_test_statistics,
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precision_recall_curves_from_test_statistics_cli,
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roc_curves,
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roc_curves_cli,
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roc_curves_from_test_statistics,
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roc_curves_from_test_statistics_cli,
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)
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# ---------------------------------------------------------------------------
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# Hyperopt
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# ---------------------------------------------------------------------------
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from ludwig.visualize.hyperopt import (
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_convert_space_to_dtype,
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hyperopt_hiplot,
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hyperopt_hiplot_cli,
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hyperopt_report,
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hyperopt_report_cli,
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hyperopt_results_to_dataframe,
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)
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# ---------------------------------------------------------------------------
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# Performance comparisons + frequency
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# ---------------------------------------------------------------------------
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from ludwig.visualize.performance import (
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compare_classifiers_multiclass_multimetric,
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compare_classifiers_multiclass_multimetric_cli,
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compare_classifiers_performance_changing_k,
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compare_classifiers_performance_changing_k_cli,
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compare_classifiers_performance_from_pred,
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compare_classifiers_performance_from_pred_cli,
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compare_classifiers_performance_from_prob,
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compare_classifiers_performance_from_prob_cli,
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compare_classifiers_performance_subset,
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compare_classifiers_performance_subset_cli,
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compare_classifiers_predictions,
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compare_classifiers_predictions_cli,
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compare_classifiers_predictions_distribution,
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compare_classifiers_predictions_distribution_cli,
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compare_performance,
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compare_performance_cli,
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frequency_vs_f1,
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frequency_vs_f1_cli,
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)
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# ---------------------------------------------------------------------------
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# Confidence thresholding + binary threshold
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# ---------------------------------------------------------------------------
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from ludwig.visualize.threshold import (
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binary_threshold_vs_metric,
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binary_threshold_vs_metric_cli,
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confidence_thresholding,
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confidence_thresholding_2thresholds_2d,
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confidence_thresholding_2thresholds_2d_cli,
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confidence_thresholding_2thresholds_3d,
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confidence_thresholding_2thresholds_3d_cli,
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confidence_thresholding_cli,
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confidence_thresholding_data_vs_acc,
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confidence_thresholding_data_vs_acc_cli,
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confidence_thresholding_data_vs_acc_subset,
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confidence_thresholding_data_vs_acc_subset_cli,
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confidence_thresholding_data_vs_acc_subset_per_class,
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confidence_thresholding_data_vs_acc_subset_per_class_cli,
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)
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# ---------------------------------------------------------------------------
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# Training / learning curves
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# ---------------------------------------------------------------------------
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from ludwig.visualize.training import (
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learning_curves,
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learning_curves_cli,
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)
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__all__ = [
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# constants
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"_PREDICTIONS_SUFFIX",
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"_PROBABILITIES_SUFFIX",
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"_CSV_SUFFIX",
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"_PARQUET_SUFFIX",
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# private helpers
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"_convert_ground_truth",
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"_vectorize_ground_truth",
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"_encode_categorical_feature",
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"_get_ground_truth_df",
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"_extract_ground_truth_values",
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"_get_cols_from_predictions",
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"_load_training_stats",
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"_validate_output_feature_name_from_train_stats",
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"_validate_output_feature_name_from_test_stats",
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# public utils
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"validate_conf_thresholds_and_probabilities_2d_3d",
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"load_data_for_viz",
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"load_training_stats_for_viz",
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"convert_to_list",
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"generate_filename_template_path",
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# training
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"learning_curves_cli",
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"learning_curves",
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# performance
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"compare_performance_cli",
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"compare_performance",
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"compare_classifiers_performance_from_prob_cli",
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"compare_classifiers_performance_from_prob",
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"compare_classifiers_performance_from_pred_cli",
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"compare_classifiers_performance_from_pred",
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"compare_classifiers_performance_subset_cli",
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"compare_classifiers_performance_subset",
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"compare_classifiers_performance_changing_k_cli",
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"compare_classifiers_performance_changing_k",
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"compare_classifiers_multiclass_multimetric_cli",
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"compare_classifiers_multiclass_multimetric",
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"compare_classifiers_predictions_cli",
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"compare_classifiers_predictions",
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"compare_classifiers_predictions_distribution_cli",
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"compare_classifiers_predictions_distribution",
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"frequency_vs_f1_cli",
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"frequency_vs_f1",
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# threshold
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"confidence_thresholding_cli",
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"confidence_thresholding",
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"confidence_thresholding_data_vs_acc_cli",
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"confidence_thresholding_data_vs_acc",
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"confidence_thresholding_data_vs_acc_subset_cli",
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"confidence_thresholding_data_vs_acc_subset",
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"confidence_thresholding_data_vs_acc_subset_per_class_cli",
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"confidence_thresholding_data_vs_acc_subset_per_class",
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"confidence_thresholding_2thresholds_2d_cli",
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"confidence_thresholding_2thresholds_2d",
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"confidence_thresholding_2thresholds_3d_cli",
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"confidence_thresholding_2thresholds_3d",
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"binary_threshold_vs_metric_cli",
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"binary_threshold_vs_metric",
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# curves
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"precision_recall_curves_cli",
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"precision_recall_curves",
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"precision_recall_curves_from_test_statistics_cli",
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"precision_recall_curves_from_test_statistics",
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"roc_curves_cli",
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"roc_curves",
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"roc_curves_from_test_statistics_cli",
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"roc_curves_from_test_statistics",
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"calibration_1_vs_all_cli",
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"calibration_1_vs_all",
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"calibration_multiclass_cli",
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"calibration_multiclass",
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# confusion
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"confusion_matrix_cli",
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"confusion_matrix",
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# hyperopt
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"hyperopt_report_cli",
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"hyperopt_report",
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"hyperopt_hiplot_cli",
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"hyperopt_hiplot",
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"_convert_space_to_dtype",
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"hyperopt_results_to_dataframe",
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# cli
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"get_visualizations_registry",
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"cli",
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]
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