mlr_measures_sim.jaccard: Jaccard Similarity Index

In mlr3: Machine Learning in R - Next Generation

Jaccard Similarity Index

Description

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

Details

For two sets A and B, the Jaccard Index is defined as

J(A, B) = \frac{|A \cap B|}{|A \cup B|}.

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

This measure is undefined if two or more sets are empty.

Dictionary

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

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

Meta Information

• Type: "similarity"

• Range: [0, 1]

• Minimize: FALSE

Note

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

mlr3 documentation built on Oct. 18, 2024, 5:11 p.m.