K-Means Clustering

kmeans {clustering}

R Documentation

K-Means Clustering

Description

Usage

kmeans(x,
    centers = 3,
    bisecting = FALSE,
    n.threads = 16,
    debug = FALSE,
    traceback = FALSE);

Arguments

numeric matrix of data, or an object that can be coerced to such a matrix (such as a numeric vector or a data frame with all numeric columns).

centers

either the number of clusters, say k, or a set of initial (distinct) cluster centres. If a number, a random set of (distinct) rows in x is chosen as the initial centres. this parameter value could be an integer value or a seed value object in clr type CanopySeeds which is produced via the canopy function.

n.threads

the parallel options, for configs the number of cpu cores for run the parallel task code. [as integer]

debug

[as boolean]

env

[as Environment]

Details

the canopy seed data is only works for the native k-means algorithm currently.

Authors

MLkit

Value

this function returns data object of type EntityClusterModel.

clr value class

EntityClusterModel

[Package clustering version 1.0.0.0 Index]