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.

## 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`

.

## Dictionary

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

:

## 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`