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Showing 5,113–5,136 of 15,976 skills
- 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
- MaxmetricCompute the MaxMetric metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MaxMetric, or asks how to score with MaxMetric.Votes: 0GitHub stars: 3
- Max ErrorCompute the max_error metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute max_error, or asks how to score with max_error.Votes: 0GitHub stars: 3
- MatthewscorrcoefCompute the MatthewsCorrCoef metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MatthewsCorrCoef, or asks how to score with MatthewsCorrCoef.Votes: 0GitHub stars: 3
- Matthews CorrcoefCompute the matthews_corrcoef metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute matthews_corrcoef, or asks how to score with matthews_corrcoef.Votes: 0GitHub stars: 3
- MatcherrorrateCompute the MatchErrorRate metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute MatchErrorRate, or asks how to score with MatchErrorRate.Votes: 0GitHub stars: 3
- Maqiuping59 Table MarkdownCompute maqiuping59/table_markdown via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of maqiuping59/table_markdown.Votes: 0GitHub stars: 3
- MannwhitneyuCompute the mannwhitneyu metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute mannwhitneyu, or asks how to score with mannwhitneyu.Votes: 0GitHub stars: 3
- LogcosherrorCompute the LogCoshError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute LogCoshError, or asks how to score with LogCoshError.Votes: 0GitHub stars: 3
- LogaucCompute the LogAUC metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute LogAUC, or asks how to score with LogAUC.Votes: 0GitHub stars: 3
- Log LossCompute the log_loss metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute log_loss, or asks how to score with log_loss.Votes: 0GitHub stars: 3
- LipvertexerrorCompute the LipVertexError metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute LipVertexError, or asks how to score with LipVertexError.Votes: 0GitHub stars: 3
- Label Ranking LossCompute the label_ranking_loss metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute label_ranking_loss, or asks how to score with label_ranking_loss.Votes: 0GitHub stars: 3
- Label Ranking Average Precision ScoreCompute the label_ranking_average_precision_score metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute label_ranking_average_precision_score, or asks how to score with label_ranking_average_precision_score.Votes: 0GitHub stars: 3
- Ks 2sampCompute the ks_2samp metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute ks_2samp, or asks how to score with ks_2samp.Votes: 0GitHub stars: 3
- Ks 1sampCompute the ks_1samp metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute ks_1samp, or asks how to score with ks_1samp.Votes: 0GitHub stars: 3
- KruskalCompute the kruskal metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute kruskal, or asks how to score with kruskal.Votes: 0GitHub stars: 3
- KldivergenceCompute the KLDivergence metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute KLDivergence, or asks how to score with KLDivergence.Votes: 0GitHub stars: 3
- KendalltauCompute the kendalltau metric — provided by scipy.stats. Use when the user has predictions and ground-truth and needs to compute kendalltau, or asks how to score with kendalltau.Votes: 0GitHub stars: 3
- KendallrankcorrcoefCompute the KendallRankCorrCoef metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute KendallRankCorrCoef, or asks how to score with KendallRankCorrCoef.Votes: 0GitHub stars: 3
- JensenshannondivergenceCompute the JensenShannonDivergence metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute JensenShannonDivergence, or asks how to score with JensenShannonDivergence.Votes: 0GitHub stars: 3
- JaccardindexCompute the JaccardIndex metric — provided by torchmetrics. Use when the user has predictions and ground-truth and needs to compute JaccardIndex, or asks how to score with JaccardIndex.Votes: 0GitHub stars: 3
- Jaccard ScoreCompute the jaccard_score metric — provided by scikit-learn. Use when the user has predictions and ground-truth and needs to compute jaccard_score, or asks how to score with jaccard_score.Votes: 0GitHub stars: 3