Description Usage Arguments Value Examples
View source: R/library neale.R
This function runs as Cluster Analysis. The first step is to run a Hierarquical Cluster, and then use centroids as starting point for the Kmeans Cluster. This function outputs the cluster ids for each line in the dataframe and a summary of the group sizes. Details of the analysis for each step are:
Hierarquical: Uses Euclidean distance and Ward's method. See more details
in hclust
.
Kmeans: Uses default options. See more details in kmeans
.
1  auto_cluster(df = NULL, grps = 3:6, name = "kmeans", iter.max = 100)

df 
A dataframe containing the variables to be used in the analysis. 
grps 
An array or number with the number of groups that should be created. 
name 
A string with the name of the variables that will be created. 
iter.max 
A number indicating the maximum number of iterations for the Kmeans cluster. 
A list with two components:
grps(dataframe): with the variables identifying the cluster each observation belongs too.
vars(dataframe): summary of the number of observations per cluster.
1  df.cluster < auto_cluster(df=df,grps=3:6,name='kmeans')

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