JaccardRate: Jaccard Rate

In hetcorFS: Unsupervised Feature Selection using the Heterogeneous Correlation Matrix

Jaccard Rate

Description

Computes the Jaccard index using Gower's dissimilarity.

Usage

JaccardRate(
  data, 
  data_red,
  k=6
)

Arguments

data	A data frame. Values of type 'numeric' or 'integer' are treated as numerical.
data_red	A data frame. A subset of data with the selected features.
k	number of neighbors

Value

Jaccard Index

numeric

References

Zhao, Z., L. Wang, and H. Liu (2010). Efficient spectral feature selection with minimum redundancy. In Proceedings of the AAAI conference on artificial intelligence, Volume 24, pp. 673–678.

Examples

data(ESI)
data=ESI[,-c(1,3,4,6,9)] ##removing categorical features
out=UFS(data,alpha=0.01,method='c',pv_adj='BH')
JR=JaccardRate(data,out$selected.features)
JR #visualize the index

hetcorFS documentation built on Nov. 24, 2025, 5:07 p.m.