A conditional entropy-based external cluster evaluation measure.

vmeasure(x, y, z = NULL, B = 1)

## Arguments

x |
A numeric vector, representing a categorical values. |

y |
A numeric vector, representing a categorical values. |

z |
A numeric matrix. A contingency table of the counts at each
combination of categorical levels. By default this argument is set to `NULL` ,
and the value of `z` is calculated based on `x` and `y` . |

B |
A numeric value. If `B` > 1 then completeness is weighted more strongly than
homogeneity, and if `B` < 1 then homogeneity is weighted more strongly than
completeness. By default this value is 1. |

## Value

A list with three elements:

"v_measure"

"homogeneity"

"completeness"

## References

Rosenberg, Andrew, and Julia Hirschberg. "V-measure:
A conditional entropy-based external cluster evaluation measure." Proceedings
of the 2007 joint conference on empirical methods in natural language
processing and computational natural language learning (EMNLP-CoNLL). 2007.

## Examples

#> Results:
#>
#> V-measure: 0.39
#> Homogeneity: 0.39
#> Completeness: 0.39