cocluster | R Documentation |
This function performs Co-Clustering (simultaneous clustering of rows and columns ) for Binary, Contingency and Continuous data-sets using latent block models.It can also be used to perform semi-supervised co-clustering.
cocluster(
data,
datatype,
semisupervised = FALSE,
rowlabels = integer(0),
collabels = integer(0),
model = NULL,
nbcocluster,
strategy = coclusterStrategy(),
nbCore = 1
)
data |
Input data as matrix (or list containing data matrix, numeric vector for row effects and numeric vector column effects in case of contingency data with known row and column effects.) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
datatype |
This is the type of data which can be "binary" , "contingency", "continuous" or "categorical". | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
semisupervised |
Boolean value specifying whether to perform semi-supervised co-clustering or not. Make sure to provide row and/or column labels if specified value is true. The default value is false. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
rowlabels |
Integer Vector specifying the class of rows. The class number starts from zero. Provide -1 for unknown row class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
collabels |
Integer Vector specifying the class of columns. The class number starts from zero. Provide -1 for unknown column class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
model |
This is the name of model. The following models exists for various types of data:
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
nbcocluster |
Integer vector specifying the number of row and column clusters respectively. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
strategy |
Object of class | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
nbCore |
number of thread to use (OpenMP must be available), 0 for all cores. Default value is 1. |
Return an object of BinaryOptions
or ContingencyOptions
or ContinuousOptions
depending on whether the data-type is Binary, Contingency or Continuous
respectively.
# Simple example with simulated binary data
#load data
data(binarydata)
#usage of cocluster function in its most simplest form
out<-cocluster(binarydata,datatype="binary",nbcocluster=c(2,3))
#Summarize the output results
summary(out)
#Plot the original and Co-clustered data
plot(out)
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