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Visualize cluster data for assorted values of k and methods such as
WSS, Silhouette and Gap Statistic. See factoextra::fviz_nbclust
for more.
clusterOptimalK(
df,
method = c("wss", "silhouette", "gap_stat"),
drop_na = TRUE,
ohse = TRUE,
norm = TRUE,
quiet = TRUE,
...
)
Plot. Optimal number of clusters of df
data.frame given a
selected method
.
Dataframe
Character vector.
Boolean. Should NA rows be removed?
Boolean. Do you wish to automatically run one hot encoding to non-numerical columns?
Boolean. Should the data be normalized?
Boolean. Keep quiet? If not, print messages.
Additional parameters passed to factoextra::fviz_nbclust
Other Clusters:
clusterKmeans()
,
clusterVisualK()
,
reduce_pca()
,
reduce_tsne()
# You must have "factoextra" library to use this auxiliary function:
if (FALSE) {
data("iris")
df <- subset(iris, select = c(-Species))
# Calculate and plot optimal k clusters
clusterOptimalK(df)
}
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