Information Theoretic Metrics for Multi-Class Predictor Evaluation (tech.magnetic.com) 13 points by dcrosta 11y ago ↗ HN
[–] brobdingnagian 11y ago ↗ I'm not entirely clear on why this was needed - The Matthews Correlation Coefficient can easily be used in multi-class multi-label classification and regression scenarios. [–] darkmighty 11y ago ↗ I'm guessing here -- because there are highly dependent uncorrelated datasets?It's easy to give examples:https://en.wikipedia.org/wiki/Normally_distributed_and_uncor... [–] [deleted] 11y ago ↗ (comment deleted) [–] aphar 11y ago ↗ https://en.wikipedia.org/wiki/Matthews_correlation_coefficie... is defined for binary (two-class) classifications only. [–] brobdingnagian 11y ago ↗ MCC is trivially extended to support regression and multi-label. See the implementation in http://grey.colorado.edu/emergent
[–] darkmighty 11y ago ↗ I'm guessing here -- because there are highly dependent uncorrelated datasets?It's easy to give examples:https://en.wikipedia.org/wiki/Normally_distributed_and_uncor...
[–] aphar 11y ago ↗ https://en.wikipedia.org/wiki/Matthews_correlation_coefficie... is defined for binary (two-class) classifications only. [–] brobdingnagian 11y ago ↗ MCC is trivially extended to support regression and multi-label. See the implementation in http://grey.colorado.edu/emergent
[–] brobdingnagian 11y ago ↗ MCC is trivially extended to support regression and multi-label. See the implementation in http://grey.colorado.edu/emergent
5 comments
[ 2.3 ms ] story [ 23.7 ms ] threadIt's easy to give examples:
https://en.wikipedia.org/wiki/Normally_distributed_and_uncor...