Metric 類別
定義分類和回歸支援的所有計量。
- 繼承
-
builtins.objectMetric
建構函式
Metric()
方法
pretty |
計量的詳細資訊名稱。 |
pretty
計量的詳細資訊名稱。
pretty(metric)
參數
名稱 | Description |
---|---|
metric
必要
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屬性
AUCBinary
AUCBinary = 'AUC_binary'
AUCMacro
AUCMacro = 'AUC_macro'
AUCMicro
AUCMicro = 'AUC_micro'
AUCWeighted
AUCWeighted = 'AUC_weighted'
Accuracy
Accuracy = 'accuracy'
AccuracyTable
AccuracyTable = 'accuracy_table'
AvgPrecisionBinary
AvgPrecisionBinary = 'average_precision_score_binary'
AvgPrecisionMacro
AvgPrecisionMacro = 'average_precision_score_macro'
AvgPrecisionMicro
AvgPrecisionMicro = 'average_precision_score_micro'
AvgPrecisionWeighted
AvgPrecisionWeighted = 'average_precision_score_weighted'
BalancedAccuracy
BalancedAccuracy = 'balanced_accuracy'
CLASSIFICATION_BALANCED_SET
CLASSIFICATION_BALANCED_SET = {'AUC_macro', 'average_precision_score_macro', 'balanced_accuracy', 'f1_score_macro', 'norm_macro_recall', 'precision_score_macro', 'recall_score_macro'}
CLASSIFICATION_BINARY_SET
CLASSIFICATION_BINARY_SET = {'AUC_binary', 'average_precision_score_binary', 'f1_score_binary', 'precision_score_binary', 'recall_score_binary'}
CLASSIFICATION_PRIMARY_SET
CLASSIFICATION_PRIMARY_SET = {'AUC_weighted', 'accuracy', 'average_precision_score_weighted', 'norm_macro_recall', 'precision_score_weighted'}
CLASSIFICATION_SET
CLASSIFICATION_SET = {'AUC_binary', 'AUC_macro', 'AUC_micro', 'AUC_weighted', 'accuracy', 'accuracy_table', 'average_precision_score_binary', 'average_precision_score_macro', 'average_precision_score_micro', 'average_precision_score_weighted', 'balanced_accuracy', 'confusion_matrix', 'f1_score_binary', 'f1_score_macro', 'f1_score_micro', 'f1_score_weighted', 'log_loss', 'matthews_correlation', 'norm_macro_recall', 'precision_score_binary', 'precision_score_macro', 'precision_score_micro', 'precision_score_weighted', 'recall_score_binary', 'recall_score_macro', 'recall_score_micro', 'recall_score_weighted', 'weighted_accuracy'}
CLIPS_NEG
CLIPS_NEG = {'explained_variance': -1, 'r2_score': -1, 'spearman_correlation': -1}
CLIPS_POS
CLIPS_POS = {'log_loss': 1, 'normalized_mean_absolute_error': 1, 'normalized_median_absolute_error': 1, 'normalized_root_mean_squared_error': 1, 'normalized_root_mean_squared_log_error': 1, 'train time': 1200}
ConfusionMatrix
ConfusionMatrix = 'confusion_matrix'
ExplainedVariance
ExplainedVariance = 'explained_variance'
F1Binary
F1Binary = 'f1_score_binary'
F1Macro
F1Macro = 'f1_score_macro'
F1Micro
F1Micro = 'f1_score_micro'
F1Weighted
F1Weighted = 'f1_score_weighted'
FORECAST_SET
FORECAST_SET = {'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table'}
FULL_SET
FULL_SET = {'AUC_binary', 'AUC_macro', 'AUC_micro', 'AUC_weighted', 'accuracy', 'accuracy_table', 'average_precision_score_binary', 'average_precision_score_macro', 'average_precision_score_micro', 'average_precision_score_weighted', 'balanced_accuracy', 'confusion_matrix', 'explained_variance', 'f1_score_binary', 'f1_score_macro', 'f1_score_micro', 'f1_score_weighted', 'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table', 'log_loss', 'matthews_correlation', 'mean_absolute_error', 'mean_absolute_percentage_error', 'mean_average_precision', 'median_absolute_error', 'norm_macro_recall', 'normalized_mean_absolute_error', 'normalized_median_absolute_error', 'normalized_root_mean_squared_error', 'normalized_root_mean_squared_log_error', 'precision_score_binary', 'precision_score_macro', 'precision_score_micro', 'precision_score_weighted', 'predicted_true', 'r2_score', 'recall_score_binary', 'recall_score_macro', 'recall_score_micro', 'recall_score_weighted', 'residuals', 'root_mean_squared_error', 'root_mean_squared_log_error', 'spearman_correlation', 'weighted_accuracy'}
ForecastAdjustmentResiduals
ForecastAdjustmentResiduals = 'forecast_adjustment_residuals'
ForecastMAPE
ForecastMAPE = 'forecast_mean_absolute_percentage_error'
ForecastResiduals
ForecastResiduals = 'forecast_residuals'
ForecastSMAPE
ForecastSMAPE = 'forecast_symmetric_mean_absolute_percentage_error'
ForecastTable
ForecastTable = 'forecast_table'
IMAGE_CLASSIFICATION_MULTILABEL_PRIMARY_SET
IMAGE_CLASSIFICATION_MULTILABEL_PRIMARY_SET = {'iou'}
IMAGE_CLASSIFICATION_PRIMARY_SET
IMAGE_CLASSIFICATION_PRIMARY_SET = {'accuracy'}
IMAGE_OBJECT_DETECTION_PRIMARY_SET
IMAGE_OBJECT_DETECTION_PRIMARY_SET = {'mean_average_precision'}
IMAGE_OBJECT_DETECTION_SET
IMAGE_OBJECT_DETECTION_SET = {'mean_average_precision'}
IOU
IOU = 'iou'
LogLoss
LogLoss = 'log_loss'
MAPE
MAPE = 'mean_absolute_percentage_error'
MatthewsCorrelation
MatthewsCorrelation = 'matthews_correlation'
MeanAbsError
MeanAbsError = 'mean_absolute_error'
MeanAveragePrecision
MeanAveragePrecision = 'mean_average_precision'
MedianAbsError
MedianAbsError = 'median_absolute_error'
NONSCALAR_CLASSIFICATION_SET
NONSCALAR_CLASSIFICATION_SET = {'accuracy_table', 'confusion_matrix'}
NONSCALAR_FORECAST_SET
NONSCALAR_FORECAST_SET = {'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table'}
NONSCALAR_FULL_SET
NONSCALAR_FULL_SET = {'accuracy_table', 'confusion_matrix', 'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table', 'predicted_true', 'residuals'}
NONSCALAR_REGRESSION_SET
NONSCALAR_REGRESSION_SET = {'predicted_true', 'residuals'}
NormMacroRecall
NormMacroRecall = 'norm_macro_recall'
NormMeanAbsError
NormMeanAbsError = 'normalized_mean_absolute_error'
NormMedianAbsError
NormMedianAbsError = 'normalized_median_absolute_error'
NormRMSE
NormRMSE = 'normalized_root_mean_squared_error'
NormRMSLE
NormRMSLE = 'normalized_root_mean_squared_log_error'
PrecisionBinary
PrecisionBinary = 'precision_score_binary'
PrecisionMacro
PrecisionMacro = 'precision_score_macro'
PrecisionMicro
PrecisionMicro = 'precision_score_micro'
PrecisionWeighted
PrecisionWeighted = 'precision_score_weighted'
PredictedTrue
PredictedTrue = 'predicted_true'
R2Score
R2Score = 'r2_score'
REGRESSION_PRIMARY_SET
REGRESSION_PRIMARY_SET = {'normalized_mean_absolute_error', 'normalized_root_mean_squared_error', 'r2_score', 'spearman_correlation'}
REGRESSION_SET
REGRESSION_SET = {'explained_variance', 'mean_absolute_error', 'mean_absolute_percentage_error', 'median_absolute_error', 'normalized_mean_absolute_error', 'normalized_median_absolute_error', 'normalized_root_mean_squared_error', 'normalized_root_mean_squared_log_error', 'predicted_true', 'r2_score', 'residuals', 'root_mean_squared_error', 'root_mean_squared_log_error', 'spearman_correlation'}
RMSE
RMSE = 'root_mean_squared_error'
RMSLE
RMSLE = 'root_mean_squared_log_error'
RecallBinary
RecallBinary = 'recall_score_binary'
RecallMacro
RecallMacro = 'recall_score_macro'
RecallMicro
RecallMicro = 'recall_score_micro'
RecallWeighted
RecallWeighted = 'recall_score_weighted'
Residuals
Residuals = 'residuals'
SAMPLE_WEIGHTS_UNSUPPORTED_SET
SAMPLE_WEIGHTS_UNSUPPORTED_SET = {'median_absolute_error', 'normalized_median_absolute_error', 'spearman_correlation', 'weighted_accuracy'}
SCALAR_CLASSIFICATION_SET
SCALAR_CLASSIFICATION_SET = {'AUC_binary', 'AUC_macro', 'AUC_micro', 'AUC_weighted', 'accuracy', 'average_precision_score_binary', 'average_precision_score_macro', 'average_precision_score_micro', 'average_precision_score_weighted', 'balanced_accuracy', 'f1_score_binary', 'f1_score_macro', 'f1_score_micro', 'f1_score_weighted', 'log_loss', 'matthews_correlation', 'norm_macro_recall', 'precision_score_binary', 'precision_score_macro', 'precision_score_micro', 'precision_score_weighted', 'recall_score_binary', 'recall_score_macro', 'recall_score_micro', 'recall_score_weighted', 'weighted_accuracy'}
SCALAR_FULL_SET
SCALAR_FULL_SET = {'AUC_binary', 'AUC_macro', 'AUC_micro', 'AUC_weighted', 'accuracy', 'average_precision_score_binary', 'average_precision_score_macro', 'average_precision_score_micro', 'average_precision_score_weighted', 'balanced_accuracy', 'explained_variance', 'f1_score_binary', 'f1_score_macro', 'f1_score_micro', 'f1_score_weighted', 'log_loss', 'matthews_correlation', 'mean_absolute_error', 'mean_absolute_percentage_error', 'median_absolute_error', 'norm_macro_recall', 'normalized_mean_absolute_error', 'normalized_median_absolute_error', 'normalized_root_mean_squared_error', 'normalized_root_mean_squared_log_error', 'precision_score_binary', 'precision_score_macro', 'precision_score_micro', 'precision_score_weighted', 'r2_score', 'recall_score_binary', 'recall_score_macro', 'recall_score_micro', 'recall_score_weighted', 'root_mean_squared_error', 'root_mean_squared_log_error', 'spearman_correlation', 'weighted_accuracy'}
SCALAR_FULL_SET_TIME
SCALAR_FULL_SET_TIME = {'AUC_binary', 'AUC_macro', 'AUC_micro', 'AUC_weighted', 'accuracy', 'average_precision_score_binary', 'average_precision_score_macro', 'average_precision_score_micro', 'average_precision_score_weighted', 'balanced_accuracy', 'explained_variance', 'f1_score_binary', 'f1_score_macro', 'f1_score_micro', 'f1_score_weighted', 'fit_time', 'log_loss', 'matthews_correlation', 'mean_absolute_error', 'mean_absolute_percentage_error', 'median_absolute_error', 'norm_macro_recall', 'normalized_mean_absolute_error', 'normalized_median_absolute_error', 'normalized_root_mean_squared_error', 'normalized_root_mean_squared_log_error', 'precision_score_binary', 'precision_score_macro', 'precision_score_micro', 'precision_score_weighted', 'predict_time', 'r2_score', 'recall_score_binary', 'recall_score_macro', 'recall_score_micro', 'recall_score_weighted', 'root_mean_squared_error', 'root_mean_squared_log_error', 'spearman_correlation', 'train time', 'weighted_accuracy'}
SCALAR_REGRESSION_SET
SCALAR_REGRESSION_SET = {'explained_variance', 'mean_absolute_error', 'mean_absolute_percentage_error', 'median_absolute_error', 'normalized_mean_absolute_error', 'normalized_median_absolute_error', 'normalized_root_mean_squared_error', 'normalized_root_mean_squared_log_error', 'r2_score', 'root_mean_squared_error', 'root_mean_squared_log_error', 'spearman_correlation'}
SCHEMA_TYPE_ACCURACY_TABLE
SCHEMA_TYPE_ACCURACY_TABLE = 'accuracy_table'
SCHEMA_TYPE_CONFUSION_MATRIX
SCHEMA_TYPE_CONFUSION_MATRIX = 'confusion_matrix'
SCHEMA_TYPE_MAPE
SCHEMA_TYPE_MAPE = 'mape_table'
SCHEMA_TYPE_PREDICTIONS
SCHEMA_TYPE_PREDICTIONS = 'predictions'
SCHEMA_TYPE_RESIDUALS
SCHEMA_TYPE_RESIDUALS = 'residuals'
SCHEMA_TYPE_SMAPE
SCHEMA_TYPE_SMAPE = 'smape_table'
SMAPE
SMAPE = 'symmetric_mean_absolute_percentage_error'
Spearman
Spearman = 'spearman_correlation'
TEXT_CLASSIFICATION_MULTILABEL_PRIMARY_SET
TEXT_CLASSIFICATION_MULTILABEL_PRIMARY_SET = {'accuracy'}
TEXT_CLASSIFICATION_PRIMARY_SET
TEXT_CLASSIFICATION_PRIMARY_SET = {'AUC_weighted', 'accuracy', 'precision_score_weighted'}
TEXT_NER_PRIMARY_SET
TEXT_NER_PRIMARY_SET = {'accuracy'}
WeightedAccuracy
WeightedAccuracy = 'weighted_accuracy'