jaccard_similarity

vector giving the first set of clusters

clus1

vector giving the second set of clusters

clus2

Compute the Jaccard similarity coefficient for two clusterings

Biclustering is a statistical learning technique that simultaneously
partitions and clusters rows and columns of a data matrix. Since the solution
space of biclustering is in infeasible to completely search with current
computational mechanisms, this package uses a greedy heuristic. The algorithm
featured in this package is, to the best our knowledge, the first biclustering
algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H.,
Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information
Sciences, 510, 304<e2><80><93>316.

John Reisner

jaccard_similarity: Compute the Jaccard similarity coefficient for two clusterings

Description

Usage

Arguments

Value

References