# Compute a linear discriminant analysis on classified cluster groups

Source:`R/cluster_discrimination.R`

`cluster_discrimination.Rd`

Computes linear discriminant analysis (LDA) on classified cluster groups, and
determines the goodness of classification for each cluster group. See `MASS::lda()`

for details.

## Arguments

- x
A data frame

- cluster_groups
Group classification of the cluster analysis, which can be retrieved from the

`cluster_analysis()`

function.- ...
Other arguments to be passed to or from.

## See also

`n_clusters()`

to determine the number of clusters to extract,
`cluster_analysis()`

to compute a cluster analysis and
`performance::check_clusterstructure()`

to check suitability of data for
clustering.

## Examples

```
# Retrieve group classification from hierarchical cluster analysis
clustering <- cluster_analysis(iris[, 1:4], n = 3)
# Goodness of group classification
cluster_discrimination(clustering)
#> # Accuracy of Cluster Group Classification via Linear Discriminant Analysis (LDA)
#>
#> Group Accuracy
#> 1 82.98%
#> 2 94.34%
#> 3 100.00%
#>
#> Overall accuracy of classification: 92.67%
#>
```