Output-class: Constructor of Output class
In Funclustering: Functional Data Clustering
Description
This class contains the parameters in the output after
running classification.
Details
- tik
a matrix of size (number of Curves)
x (K), each column contains the weights of the curves in
the corresponding class.
- cls
a vector of size
number of curves, containing the index of the class for
each curve.
- proportion
a matrix of size 1xnbClust
(number of clusters), containing the estimated mixture
proportions.
- loglikelihood
the estimated
log-likelihood.
- aic
the value of AIC criterion.
- bic
the value of BIC criterion.
- icl
the
value of ICL criterion.
- dimensions
a vector of
size nbClust of the dimensions of the specifique
dimensions of the functional data in each class.
- dimTotal
a matrix of size nbClust x
nbRunIteration, where nbRunIteration is the number of
iterations before the algorithm converge. Each column of
the dimTotal matrix contain the dimensions on the
coresponding iteration.
- V
principal components
variances per cluster
- empty
logical parameter,
and empty=TRUE if we have an empty class
Funclustering documentation built on Nov. 25, 2018, 1:04 a.m.
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Description
This class contains the parameters in the output after running classification.
Details
- tik
a matrix of size (number of Curves) x (K), each column contains the weights of the curves in the corresponding class.
- cls
a vector of size number of curves, containing the index of the class for each curve.
- proportion
a matrix of size 1xnbClust (number of clusters), containing the estimated mixture proportions.
- loglikelihood
the estimated log-likelihood.
- aic
the value of AIC criterion.
- bic
the value of BIC criterion.
- icl
the value of ICL criterion.
- dimensions
a vector of size nbClust of the dimensions of the specifique dimensions of the functional data in each class.
- dimTotal
a matrix of size nbClust x nbRunIteration, where nbRunIteration is the number of iterations before the algorithm converge. Each column of the dimTotal matrix contain the dimensions on the coresponding iteration.
- V
principal components variances per cluster
- empty
logical parameter, and empty=TRUE if we have an empty class
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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