cluster_plot | R Documentation |
Kmeans clustering is performed using add_clusters.
cluster_plot(
data,
cols,
newcol = NULL,
k = NULL,
method = NULL,
labels = TRUE,
clean = TRUE,
...
)
data |
A tibble. |
cols |
A tidy selection of item columns or a single column with cluster values as a factor. If the column already contains a cluster result from add_clusters, it is used, and other parameters are ignored. If no cluster result exists, it is calculated with add_clusters. |
newcol |
Name of the new cluster column as a character vector. Set to NULL (default) to automatically build a name from the common column prefix, prefixed with "cls_". |
k |
Number of clusters to calculate.
Set to NULL to output a scree plot for up to 10 clusters
and automatically choose the number of clusters based on the elbow criterion.
The within-sums of squares for the scree plot are calculated by
|
method |
The method as character value. Currently, only kmeans is supported.
All items are scaled before performing the cluster analysis using
|
labels |
If TRUE (default) extracts labels from the attributes, see codebook. |
clean |
Prepare data by data_clean. |
... |
Placeholder to allow calling the method with unused parameters from plot_metrics. |
A ggplot object.
library(volker)
data <- volker::chatgpt
cluster_plot(data, starts_with("cg_adoption"), k = 2)
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