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        README.md
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            tags:
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            - evaluate
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            - metric
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            ---
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            # Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
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            tags:
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            - evaluate
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            - metric
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            description: >-
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              The Spearman rank-order correlation coefficient is a measure of the
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              relationship between two datasets. Like other correlation coefficients,
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              this one varies between -1 and +1 with 0 implying no correlation.
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              Positive correlations imply that as data in dataset x increases, so
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              does data in dataset y. Negative correlations imply that as x increases,
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              y decreases. Correlations of -1 or +1 imply an exact monotonic relationship.
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              Unlike the Pearson correlation, the Spearman correlation does not
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              assume that both datasets are normally distributed.
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              The p-value roughly indicates the probability of an uncorrelated system
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              producing datasets that have a Spearman correlation at least as extreme
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              as the one computed from these datasets. The p-values are not entirely
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              reliable but are probably reasonable for datasets larger than 500 or so.
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            ---
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            # Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
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