reduce_cluster: Reduce the amount of data through using kmeans clustering...

In MalachiTimothyPhillips/ggfast: Gotta Go Fast (ggfast)

Description

Reduce the amount of data through using kmeans clustering algorithm Call the in R kmean cluster function in order to reduce a pool of data into a few, clustered points

Usage

reduce_cluster(x, k, fileName, iter.max = 10, nstart = 1,
  algorithm = "Lloyd", trace = FALSE)

Arguments

x	Data in the form of a data frame or data matrix, for safety, please use data.matrix(...) as a wrapper
k	Number of clusters to form
fileName	Name of file you wish to save a .csv formatted file to
iter.max	Number of iterations to use at a maximum (default = 10)
nstart	How many random sets to be chosen
algorithm	What algorithm to use (default="Lloyd"). choices include: "Hartigan-Wong", "LLoyd", "MacQueen", and "Forgy"
trace	logical or integer number, currently only used in the default method ("Hartigan-Wong"): if positive (or true), tracing information on the progress of the algorithm is produced. Higher values may produce more tracing information. @examples reduce_cluster(data.matrix(iris), 10, "myFile.csv") reduce_cluster(df, 15, "myManyIterationsFile.csv", iter.max=1000, algorithm="MacQueen")

MalachiTimothyPhillips/ggfast documentation built on May 18, 2019, 11:27 p.m.