mlr_measures_sim.phi: Phi Coefficient Similarity

In mlr-org/mlr3: Machine Learning in R - Next Generation

Phi Coefficient Similarity

Description

Measure to compare two or more sets w.r.t. their similarity.

Details

The Phi Coefficient is defined as the Pearson correlation between the binary representation of two sets A and B. The binary representation for A is a logical vector of length p with the i-th element being 1 if the corresponding element is in A, and 0 otherwise.

If more than two sets are provided, the mean of all pairwise scores is calculated.

This measure is undefined if one set contains none or all possible elements.

Parameters

Id	Type	Default	Range
p	integer	-	[1, \infty)

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

mlr_measures$get("sim.phi")
msr("sim.phi")

Meta Information

• Type: "similarity"

• Range: [-1, 1]

• Minimize: FALSE

Note

This measure requires learners with property "selected_features". The extracted feature sets are passed to mlr3measures::phi() from package mlr3measures.

If the measure is undefined for the input, NaN is returned. This can be customized by setting the field na_value.

See Also

Dictionary of Measures: mlr_measures

as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.

Other similarity measures: mlr_measures_sim.jaccard

mlr-org/mlr3 documentation built on July 4, 2025, 3:40 a.m.