get_random {adproclus}

Generate initial random start

Description

Generate an initial random start for the (low dimensional) Additive Profile Clustering algorithm (see adproclus and adproclus_low_dim).

Usage

get_random(data, nclusters, seed = NULL)

Arguments

data

Object-by-variable data matrix of class matrix or data.frame.

nclusters

Number of clusters to be used. Must be a positive integer.

seed

Integer. Seed for the random number generator. Default: NULL

Details

get_random generates a random initial binary membership matrix A such that each entry is an independen draw from a Bernoulli Distribution with \pi = 0.5.

For generating an initial start from random draws from the data, see get_semirandom. For generating an initial start based on a specific set of initial cluster centers, see get_rational.

Warning: This function does not obtain an ADPRCOLUS model. To perform aditive profile clustering, see adproclus.

Value

get_random() returns a list with the following components:

type

A character string denoting the type of start ('Random Start')

A

A randomly generated initial Membership matrix

References

Wilderjans, T. F., Ceulemans, E., Van Mechelen, I., & Depril, D. (2010). ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices. Behavior Research Methods, 43(1), 56-65.

Depril, D., Van Mechelen, I., & Mirkin, B. (2008). Algorithms for additive clustering of rectangular data tables. Computational Statistics and Data Analysis, 52, 4923-4938.

Depril, D., Van Mechelen, I., & Wilderjans, T. F. (2012). Lowdimensional additive overlapping clustering. Journal of classification, 29, 297-320.

See Also

adproclus, adproclus_low_dim

for details about membership and profile matrices

get_semirandom

for generating semi-random starts

get_rational

for generating rational starts

Examples

# Obtain data from data set "Stackloss" and generate start allocation
start_allocation <- get_random(stackloss, 3)$A