generate.sample1: Sample1 generator of synthetic data

In clusterv: Assessment of Cluster Stability by Randomized Maps

Sample1 generator of synthetic data

Description

Multivariate normally distributed data synthetic generator. Data sets with 3 clusters are randomly generated. n examples for each class are generated. All classes (each one of n examples) have their last dim-500 variables centered in 0. The first class (first n examples) has its first 500 features centered in 0. The second class (second n examples) has its first 500 features centered in m. The third class (last n examples) has its first 500 features centered in -m. For all classes the covariance matrix is diagonal with all values on the diagonal equal to sigma.

Usage

generate.sample1(n = 2, m = 6, sigma = 1, dim = 10000)

Arguments

n	number of examples for each class
m	center of the first 500 variables of the second class
sigma	value of the diagonal elements of the covariance matrix
dim	number of variables (features)

Value

a matrix with dim rows (variables) and n*3 columns (examples)

Author(s)

Giorgio Valentini [e-mail]

Examples

generate.sample1()
# Generation of a data set with 30 1000-dimensional examples, with the examples 
# of the first class  centered in 0 for the first 500 variables, the second class 
# is centered in 1 for the first 500 variables, the third in -1.  
# The covariance matrix is the matrix with all  values different from 0 (equal to 3)
# on the diagonal elements.
generate.sample1(n = 10, m = 1, sigma = 3, dim = 1000)

clusterv documentation built on June 8, 2025, 10:21 a.m.