KmeansClust: K-Means Clustering

In admurali/self: Simple Exploratory Learning Framework

Description

K-Means Clustering

Usage

KmeansClust(data, x, y, cluster, rstart = 1)

Arguments

data	is the dataset containing the observations.
x	is a reference to a column in the dataset that is could be the independent variable.
y	is a reference to another column in the dataset that could be the dependent variable.
cluster	is the number of clusters to perform k-means operation on.
rstart	is how many random starting cluster assignments to try before choosing the one with the lowest within cluster variation

Details

Subsets given data using column names or number and performs k-means clustering on the subset data with error handling.

Value

Returns a list that contains values corresponding to the cluster number, and other details.

Author(s)

Adithya Murali

See Also

kmeans

Examples

print(KmeansClustList(iris, 'Sepal.Length', "Sepal.Width", 3))

admurali/self documentation built on May 10, 2019, 5:56 a.m.