Metric Classe

Nomes verbosos para métricas.

pretty(metric)

Parâmetros

AUCBinary = 'AUC_binary'

AUCMacro = 'AUC_macro'

AUCMicro = 'AUC_micro'

AUCWeighted = 'AUC_weighted'

Accuracy = 'accuracy'

AccuracyTable = 'accuracy_table'

AvgPrecisionBinary = 'average_precision_score_binary'

AvgPrecisionMacro = 'average_precision_score_macro'

AvgPrecisionMicro = 'average_precision_score_micro'

AvgPrecisionWeighted = 'average_precision_score_weighted'

BalancedAccuracy = 'balanced_accuracy'

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 = {'AUC_binary', 'average_precision_score_binary', 'f1_score_binary', 'precision_score_binary', 'recall_score_binary'}

CLASSIFICATION_PRIMARY_SET = {'AUC_weighted', 'accuracy', 'average_precision_score_weighted', 'norm_macro_recall', 'precision_score_weighted'}

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 = {'explained_variance': -1, 'r2_score': -1, 'spearman_correlation': -1}

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 = 'confusion_matrix'

ExplainedVariance = 'explained_variance'

F1Binary = 'f1_score_binary'

F1Macro = 'f1_score_macro'

F1Micro = 'f1_score_micro'

F1Weighted = 'f1_score_weighted'

FORECAST_SET = {'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table'}

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 = 'forecast_adjustment_residuals'

ForecastMAPE = 'forecast_mean_absolute_percentage_error'

ForecastResiduals = 'forecast_residuals'

ForecastSMAPE = 'forecast_symmetric_mean_absolute_percentage_error'

ForecastTable = 'forecast_table'

IMAGE_CLASSIFICATION_MULTILABEL_PRIMARY_SET = {'iou'}

IMAGE_CLASSIFICATION_PRIMARY_SET = {'accuracy'}

IMAGE_OBJECT_DETECTION_PRIMARY_SET = {'mean_average_precision'}

IMAGE_OBJECT_DETECTION_SET = {'mean_average_precision'}

IOU = 'iou'

LogLoss = 'log_loss'

MAPE = 'mean_absolute_percentage_error'

MatthewsCorrelation = 'matthews_correlation'

MeanAbsError = 'mean_absolute_error'

MeanAveragePrecision = 'mean_average_precision'

MedianAbsError = 'median_absolute_error'

NONSCALAR_CLASSIFICATION_SET = {'accuracy_table', 'confusion_matrix'}

NONSCALAR_FORECAST_SET = {'forecast_adjustment_residuals', 'forecast_mean_absolute_percentage_error', 'forecast_residuals', 'forecast_table'}

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 = {'predicted_true', 'residuals'}

NormMacroRecall = 'norm_macro_recall'

NormMeanAbsError = 'normalized_mean_absolute_error'

NormMedianAbsError = 'normalized_median_absolute_error'

NormRMSE = 'normalized_root_mean_squared_error'

NormRMSLE = 'normalized_root_mean_squared_log_error'

PrecisionBinary = 'precision_score_binary'

PrecisionMacro = 'precision_score_macro'

PrecisionMicro = 'precision_score_micro'

PrecisionWeighted = 'precision_score_weighted'

PredictedTrue = 'predicted_true'

R2Score = 'r2_score'

REGRESSION_PRIMARY_SET = {'normalized_mean_absolute_error', 'normalized_root_mean_squared_error', 'r2_score', 'spearman_correlation'}

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 = 'root_mean_squared_error'

RMSLE = 'root_mean_squared_log_error'

RecallBinary = 'recall_score_binary'

RecallMacro = 'recall_score_macro'

RecallMicro = 'recall_score_micro'

RecallWeighted = 'recall_score_weighted'

Residuals = 'residuals'

SAMPLE_WEIGHTS_UNSUPPORTED_SET = {'median_absolute_error', 'normalized_median_absolute_error', 'spearman_correlation', 'weighted_accuracy'}

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 = {'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 = {'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 = {'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 = 'accuracy_table'

SCHEMA_TYPE_CONFUSION_MATRIX = 'confusion_matrix'

SCHEMA_TYPE_MAPE = 'mape_table'

SCHEMA_TYPE_PREDICTIONS = 'predictions'

SCHEMA_TYPE_RESIDUALS = 'residuals'

SCHEMA_TYPE_SMAPE = 'smape_table'

SMAPE = 'symmetric_mean_absolute_percentage_error'

Spearman = 'spearman_correlation'

TEXT_CLASSIFICATION_MULTILABEL_PRIMARY_SET = {'accuracy'}

TEXT_CLASSIFICATION_PRIMARY_SET = {'AUC_weighted', 'accuracy', 'precision_score_weighted'}

TEXT_NER_PRIMARY_SET = {'accuracy'}

WeightedAccuracy = 'weighted_accuracy'