getFuzzyPartitionElementMetrics

Computes a selection of external fuzzy clustering evaluation metrics at the element level.

Usage

getFuzzyPartitionElementMetrics(
  hardTrue = NULL,
  fuzzyTrue = NULL,
  hardPred = NULL,
  fuzzyPred = NULL,
  fuzzy_true = TRUE,
  fuzzy_pred = FALSE,
  metrics = c("fuzzySPC"),
  useNegatives = TRUE,
  verbose = TRUE,
  usePairs = TRUE
)

Arguments

hardTrue

A vector of true cluster labels

fuzzyTrue

A object coercible to a numeric matrix with membership probability of elements (rows) in clusters (columns). Must have the same number of rows as the length of hardTrue.

hardPred

A vector of predicted cluster labels

fuzzyPred

A object coercible to a numeric matrix with membership probability of elements (rows) in clusters (columns).

fuzzy_true

Logical; whether the truth is fuzzy.

fuzzy_pred

Logical; whether the prediction is fuzzy.

metrics

The metrics to compute. Currently only "fuzzySPC" is included at the element level.

useNegatives

Logical; whether to include negative pairs in the concordance score (tends to result in a larger overall concordance and lower dynamic range of the score). Default TRUE.

verbose

Logical; whether to print expected memory usage for large datasets.

usePairs

Logical; whether to compute over pairs instead of elements. Only useful when fuzzy_true=TRUE and fuzzy_pred=FALSE.

Value

A dataframe of metric values.