R: Confusion Matrix - External Measures, Cluster Stability

confusion.matrix {clv} | R Documentation

## Confusion Matrix - External Measures, Cluster Stability

### Description

For two different partitioning function computes confusion matrix.

### Usage

    confusion.matrix(clust1, clust2)

### Arguments

`clust1` | integer `vector` with information about cluster id the object is assigned to. If vector is not integer type, it will be coerced with warning.
`clust2` | integer `vector` with information about cluster id the object is assigned to. If vector is not integer type, it will be coerced with warning.

### Details

Let P and P' be two different partitioning of the same data. Partitionings are represent as two vectors `clust1, clust2`. Both vectors should have the same length. Confusion matrix measures the size of intersection between clusters comming from P and P' according to equation:

M[i,j] = | intersection of P(i) and P'(j) |

where:

P(i) | - cluster which belongs to partitioning P,
P'(j) | - cluster which belongs to partitioning P',
|A| | - cardinality of set A.

### Value

`cls.set.section` returns a n x m integer `matrix` where n = |P| and m = |P'| defined above.

### Author(s)

Lukasz Nieweglowski

### See Also

Result used in `similarity.index`.

### Examples

    # create two different subsamples
    mx1 <- matrix(as.integer( c(1,2,3,4,5,6,1,1,2,2,3,3) ), 6, 2 )
    mx2 <- matrix(as.integer( c(1,2,4,5,6,7,1,1,2,2,3,3) ), 6, 2 )
    # find section
    m = cls.set.section(mx1,mx2)
    confusion.matrix(as.integer(m[,2]),as.integer(m[,3]))

[Package clv version 0.3-2.2 Index]