ccls {conclust} R Documentation

## Pairwise Constrained Clustering by Local Search

### Description

This function takes an unlabeled dataset and two lists of must-link and cannot-link constraints as input and produce a clustering as output.

### Usage

ccls(data, k = -1, mustLink, cantLink, maxIter = 1, tabuIter = 100, tabuLength = 20)


### Arguments

 data The unlabeled dataset. k Number of clusters. mustLink A list of must-link constraints cantLink A list of cannot-link constraints maxIter Number of iteration tabuIter Number of iteration in Tabu search tabuLength The number of elements in the Tabu list

### Details

This algorithm minimizes the clustering cost function using Tabu search.

### Value

A vector that represents the labels (clusters) of the data points

### Note

This is the first algorithm for pairwise constrained clustering by local search.

### Author(s)

Tran Khanh Hiep Nguyen Minh Duc

### References

Tran Khanh Hiep, Nguyen Minh Duc, Bui Quoc Trung (2016), Pairwise Constrained Clustering by Local Search.

Tran Khanh Hiep, Nguyen Minh Duc, Bui Quoc Trung (2016), Pairwise Constrained Clustering by Local Search.

### Examples

data = matrix(c(0, 1, 1, 0, 0, 0, 1, 1), nrow = 4)
mustLink = matrix(c(1, 2), nrow = 1)
cantLink = matrix(c(1, 4), nrow = 1)
k = 2