Python code to quickly visualize critical distances between methods after Friedman and post-hoc Nemenyi tests as introduced in Gj. Madjarov, et al., An extensive experimental comparison of methods for multi-label learning, Pattern Recognition (2012), doi:10.1016/j.patcog.2012.03.004
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Quickly visualize critical distance between methods after Friedman and post-hoc Nemenyi tests
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niedakh/algorithms-critical-distance-visualization
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Quickly visualize critical distance between methods after Friedman and post-hoc Nemenyi tests
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