Package index
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getEmbeddingMetrics()
- Compute embedding-based metrics
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getGraphMetrics()
- Compute graph-based metrics
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getPartitionMetrics()
- Compute partition-based metrics
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getFuzzyPartitionMetrics()
- Compute external metrics for fuzzy clusterings
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getSpatialExternalMetrics()
- Compute external metrics for spatial data
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getSpatialInternalMetrics()
- Compute internal metrics for spatial data
Functions for individual metrics
These are some useful functions for calculating individual metrics.
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fuzzyHardMetrics()
- Compute fuzzy-hard versions of pair-sorting partition metrics
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fuzzyPartitionMetrics()
- Compute fuzzy-fuzzy versions of pair-sorting partition metrics
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fuzzyHardSpotConcordance()
- Per-element maximal concordance between a hard and a fuzzy partition
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fuzzySpotConcordance()
- Per-element concordance between two fuzzy partitions
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getPairConcordance()
- Per-element pair concordance score
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getNeighboringPairConcordance()
- Per-element local concordance between a clustering and a ground truth
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noisy_moon
- The noisy moon dataset
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sp_toys
- Toy examples of spatial data
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toyExamples
- Toy embedding examples
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metric_info
- Metrics Information
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mockData()
- Generate mock multidimensional data
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matchSets()
- Match two partitions using Hungarian algorithm
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knnComposition()
- Compute neighborhood composition
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getFuzzyLabel()
- Get fuzzy representation of labels
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findSpatialKNN()
- Find the k nearest spatial neighbors
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emb2knn()
- Computes k nearest neighbors from embedding
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emb2snn()
- Computes shared nearest neighbors from embedding