| Type: | Package |
| Title: | Spectral Clustering for Mixed Type Data |
| Version: | 1.0.1 |
| Maintainer: | Cristina Tortora <grikris1@gmail.com> |
| Description: | Performs cluster analysis of mixed-type data using Spectral Clustering, see F. Mbuga and, C. Tortora (2022) <doi:10.3390/stats5010001>. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Depends: | R (≥ 3.5) |
| Imports: | RSpectra, cluster, ggplot2, GGally |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.2 |
| NeedsCompilation: | no |
| Packaged: | 2023-08-30 22:51:36 UTC; cristina |
| Author: | Cristina Tortora 
[aut, cre, cph],
Felix Mbuga [aut],
Zander Bonnet [aut] |
| Repository: | CRAN |
| Date/Publication: | 2023-08-30 23:10:02 UTC |
SpectralClMix
Description
Cluster analysis of mixed-type data using Spectral Clustering.
Author(s)
Felix Mbuga, Cristina Tortora, Zander Bonnet
References
F. Mbuga and, C. Tortora. Spectral Clustering of Mixed-Type Data. Stats, 5(1) 2022
Preforms spectral clustering on mix typed data
Description
Preforms spectral clustering of mix-type data
Usage
mspec(
z,
k = 2,
sigma = c(20, 20),
c_wt = NULL,
starts = 10,
its = 300,
verbose = FALSE
)
Arguments
z |
data to be clustered |
k |
the number of clusters. |
sigma |
vector of lower,upper bounds for sigma |
c_wt |
the category weights, is assigned to c(0.9999, 0.999, .99, seq(0.95, 0.05,-0.05), .01, 0.001, 0.0001) if null. |
starts |
the number of random starts |
its |
the max number of iterations for the kmeans algorithm |
verbose |
if you would like printed output during running of function |
Value
A class SpectralClMixed list with components
ct_wt |
the selected category weight |
bt/wt_ss |
the between divided by the within sum of squares |
tot_wt_ss |
the total within sum of squares |
cluster |
the cluster assignments |
data |
the original data |
References
F. Mbuga and, C. Tortora. Spectral Clustering of Mixed-Type Data. Stats, 5(1) 2022
Examples
c1=data.frame(v1=rnorm(30,0),v2=rnorm(30,0),v3=factor(round(runif(30))+1))
c2=data.frame(v1=rnorm(30,2),v2=rnorm(30,4),v3=factor(round(runif(30))+4))
data=rbind(c1,c2)
res=mspec(data, k = 2)
summary(res)
plot(res)
Plots the output of mspec
Description
Plots the output of the function mspec, which performs Spectral clustering for mixed type data. The function displays up to 10 variables on a parrallel coordinate plot and on a scatter plot matrix, with colors representing the clustering partition
Usage
## S3 method for class 'SpectralClMixed'
plot(x,cols=NULL,...)
Arguments
x |
object of SpectralClMixed class, the output of mspec |
cols |
For datasets with more than 10 columns, columns to plot |
... |
other graphic parameters |
Value
No return value,the function produces a parallel coordinate plot and a scatter plot matrix
Examples
ex1=mspec(iris,3)
plot(ex1,cols=1:4)Summarizes the output of mspec
Description
Summarizes the output of mspec
Usage
## S3 method for class 'SpectralClMixed'
summary(object,...)
Arguments
object |
object of SpectralClMixed class, the output of mspec |
... |
other optional parameters |
Value
It displays: The selected categorical variables weight, The between divided by within sum of squares, The total within sum of squares, and the cluster size.