Comments (1)
This is a method to build matrix where each cell has 0 if the two input vectors classified a pair in the same cluster, and 1 if there is no match. IIRC the same can be achieved building a contingency matrix - and probably it would be more easier to read, but as this Rand Index seems to be more theoretical than practical (this is explained in the Chapter) I moved to Adjusted Rand Index.
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Related Issues (12)
- Better readme please HOT 1
- Replace prefix ML with AI HOT 1
- Add Poisson, Gamma, Tweedie metrics to regression metrics
- Add Explained variance score to regression metrics
- Add precision, recall, and F-measurements
- Can you explain how the metric is computed
- #'as yet unclassified' HOT 1
- Having a dependency on the full polymath looks too large to me. HOT 1
- Should not we move testTake to Polymath? HOT 2
- Why Array defines sumMatrix HOT 1
- initializeWithClusterA: firstCluster clusterB: secondCluster assertion logic HOT 1
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