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- MulticlasscohenkappaCompute the MulticlassCohenKappa metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MulticlassCohenKappa, or asks how to score with MulticlassCohenKappa.Votes: 0GitHub stars: 3
- MulticlasscalibrationerrorCompute the MulticlassCalibrationError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MulticlassCalibrationError, or asks how to score with MulticlassCalibrationError.Votes: 0GitHub stars: 3
- MulticlassaverageprecisionCompute the MulticlassAveragePrecision metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MulticlassAveragePrecision, or asks how to score with MulticlassAveragePrecision.Votes: 0GitHub stars: 3
- MulticlassaurocCompute the MulticlassAUROC metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MulticlassAUROC, or asks how to score with MulticlassAUROC.Votes: 0GitHub stars: 3
- MulticlassaccuracyCompute the MulticlassAccuracy metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MulticlassAccuracy, or asks how to score with MulticlassAccuracy.Votes: 0GitHub stars: 3
- ModifiedpanopticqualityCompute the ModifiedPanopticQuality metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute ModifiedPanopticQuality, or asks how to score with ModifiedPanopticQuality.Votes: 0GitHub stars: 3
- MinmetricCompute the MinMetric metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MinMetric, or asks how to score with MinMetric.Votes: 0GitHub stars: 3
- MinmaxmetricCompute the MinMaxMetric metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MinMaxMetric, or asks how to score with MinMaxMetric.Votes: 0GitHub stars: 3
- MinkowskidistanceCompute the MinkowskiDistance metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MinkowskiDistance, or asks how to score with MinkowskiDistance.Votes: 0GitHub stars: 3
- MemorizationinformedfrechetinceptiondistanceCompute the MemorizationInformedFrechetInceptionDistance metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MemorizationInformedFrechetInceptionDistance, or asks how to score with MemorizationInformedFrechetInceptionDistance.Votes: 0GitHub stars: 3
- Median Absolute ErrorCompute the median_absolute_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute median_absolute_error, or asks how to score with median_absolute_error.Votes: 0GitHub stars: 3
- MeansquaredlogerrorCompute the MeanSquaredLogError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MeanSquaredLogError, or asks how to score with MeanSquaredLogError.Votes: 0GitHub stars: 3
- MeansquarederrorCompute the MeanSquaredError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MeanSquaredError, or asks how to score with MeanSquaredError.Votes: 0GitHub stars: 3
- MeanmetricCompute the MeanMetric metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MeanMetric, or asks how to score with MeanMetric.Votes: 0GitHub stars: 3
- MeanabsolutepercentageerrorCompute the MeanAbsolutePercentageError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MeanAbsolutePercentageError, or asks how to score with MeanAbsolutePercentageError.Votes: 0GitHub stars: 3
- MeanabsoluteerrorCompute the MeanAbsoluteError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MeanAbsoluteError, or asks how to score with MeanAbsoluteError.Votes: 0GitHub stars: 3
- Mean Tweedie DevianceCompute the mean_tweedie_deviance metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_tweedie_deviance, or asks how to score with mean_tweedie_deviance.Votes: 0GitHub stars: 3
- Mean Squared Log ErrorCompute the mean_squared_log_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_squared_log_error, or asks how to score with mean_squared_log_error.Votes: 0GitHub stars: 3
- Mean Squared ErrorCompute the mean_squared_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_squared_error, or asks how to score with mean_squared_error.Votes: 0GitHub stars: 3
- Mean Poisson DevianceCompute the mean_poisson_deviance metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_poisson_deviance, or asks how to score with mean_poisson_deviance.Votes: 0GitHub stars: 3
- Mean Pinball LossCompute the mean_pinball_loss metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_pinball_loss, or asks how to score with mean_pinball_loss.Votes: 0GitHub stars: 3
- Mean Gamma DevianceCompute the mean_gamma_deviance metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_gamma_deviance, or asks how to score with mean_gamma_deviance.Votes: 0GitHub stars: 3
- Mean Absolute Percentage ErrorCompute the mean_absolute_percentage_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_absolute_percentage_error, or asks how to score with mean_absolute_percentage_error.Votes: 0GitHub stars: 3
- Mean Absolute ErrorCompute the mean_absolute_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute mean_absolute_error, or asks how to score with mean_absolute_error.Votes: 0GitHub stars: 3