Apply all clustering methods to a precision object

This function applies all clustering methods to the training data contained in a precision object. The clustering results are added to the corresponding cluster.result slot in the object for each training dataset.

Usage

cluster.all(object, k = NULL)

Arguments

object

A precision object containing harmonized training data in the slot harmon.train.data.

k

Integer. Number of clusters. If NULL or not given, uses the number of unique labels in training data.

Value

Updated precision object with all clustering results added to the cluster.result slot.

Details

The following clustering methods are applied to the data:

• Hierarchical Clustering using multiple distance metrics (Euclidean, Pearson, and Spearman) (cluster.hc)

• Gaussian Mixture Models (MNM) (cluster.mnm)

• K-Means Clustering (cluster.kmeans)

• Self-Organizing Maps (cluster.som)

• Partitioning Around Medoids (Euclidean, Pearson, and Spearman) (cluster.pam)