kmeans_report: Plot data according to cluster assigments
In UBC-MDS/kmeans_R: R package aimed towards a user-friendly way of exploring and implementing k-means clustering.
Description
Usage
Arguments
Value
Examples
Description
Plot data according to cluster assigments
Usage
1
kmeans_report(clustered_data)
Arguments
clustered_data
– the data object (data frame or matrix) that k-means clustering has been applied to
Value
plot – a scatter plot of the data coloured by cluster assignment (if 2D data)
– a data frame reporting points and their cluster assignemnts
Examples
1
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x <- runif(100, min = 0, max = 10) + rep(c(0, 10), 50)
y <- rnorm(100, 5, 1) + rep(c(0, 10), 50)
data = data.frame(x = x, y = y)
centers <- kmeans_init(data = data, K = 2)
clustered_data <- kmeans_cluster(data=data, centers=centers)
kmeans_report(clustered_data)
UBC-MDS/kmeans_R documentation built on May 22, 2019, 2:26 p.m.
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Description Usage Arguments Value Examples
Description
Plot data according to cluster assigments
Usage
1 | kmeans_report(clustered_data)
|
Arguments
clustered_data |
– the data object (data frame or matrix) that k-means clustering has been applied to |
Value
plot – a scatter plot of the data coloured by cluster assignment (if 2D data) – a data frame reporting points and their cluster assignemnts
Examples
1 2 3 4 5 6 7 | x <- runif(100, min = 0, max = 10) + rep(c(0, 10), 50)
y <- rnorm(100, 5, 1) + rep(c(0, 10), 50)
data = data.frame(x = x, y = y)
centers <- kmeans_init(data = data, K = 2)
clustered_data <- kmeans_cluster(data=data, centers=centers)
kmeans_report(clustered_data)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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