test


This test dataset contains 3 clusters centered around (-1,2),(2,0) and (-1,-2) in a 2-dimensional space. Each cluster consists of 50 samples that were drawn from bivariate normal distributions with a common identity covariance matrix.


datasets

Implementing the Progeny Clustering algorithm, the 'progenyClust' package assesses the clustering stability and identifies the optimal clustering number for a given data matrix. It uses k-means clustering as a default, provides a tailored hierarchical clustering function, and can be customized to work with other clustering algorithms and different parameter settings. The package includes a main function progenyClust(), plot and summary methods for 'progenyClust' object, a function hclust.progenyClust() for hierarchical clustering, and two example datasets (test and cell) for testing.

C.W. Hu

progenyClust

Finding the Optimal Cluster Number Using Progeny Clustering

test function

A data frame with 150 observations on the following 2 variables. 
  <dl>
  <dt>V1</dt><dd>numeric vector of coordinates in x axis</dd> <dt>V2</dt><dd>numeric vector of coordinates in y axis</dd> </dl> 

test: 3-cluster 2-dimensional test dataset

Description

Usage

Arguments

Format

References

Examples