get_PCA: PCA visualisation
In adrienPAVOINE/ClustCheck: Clustering check and interpretation
Description
Usage
Arguments
Value
Examples
View source: R/ComponentAnalysis.R
Description
Applying a principal component analysis (PCA) to the feature variables
Usage
1
get_PCA(object)
Arguments
object
an object of class ccdata
Value
Displays three graphs to allow a synthetic view of the data
A. Represents the correlation chart between all the variables
B. split into two graphs. On the left: the correlation circle and on the right: the biplot of the individuals and variables grouped by their clusters
Examples
1
2
3
data(BankCustomer)
obj <- Dataset(BankCustomer, BankCustomer$Cluster)
get_PCA(obj)
adrienPAVOINE/ClustCheck documentation built on Dec. 31, 2020, 6:45 p.m.
R Package Documentation
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Description Usage Arguments Value Examples
View source: R/ComponentAnalysis.R
Description
Applying a principal component analysis (PCA) to the feature variables
Usage
1 | get_PCA(object)
|
Arguments
object |
an object of class ccdata |
Value
Displays three graphs to allow a synthetic view of the data A. Represents the correlation chart between all the variables B. split into two graphs. On the left: the correlation circle and on the right: the biplot of the individuals and variables grouped by their clusters
Examples
1 2 3 | data(BankCustomer)
obj <- Dataset(BankCustomer, BankCustomer$Cluster)
get_PCA(obj)
|
R Package Documentation
Browse R Packages
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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