H2OClusteringModel-class: The H2OClusteringModel object.
In h2o: R Interface for the 'H2O' Scalable Machine Learning Platform
H2OClusteringModel-class R Documentation
The H2OClusteringModel object.
Description
This virtual class represents a clustering model built by H2O.
Details
This object has slots for the key, which is a character string that points to the model key existing in the H2O cluster,
the data used to build the model (an object of class H2OFrame).
Slots
model_idA character string specifying the key for the model fit in the H2O cluster's key-value store.
algorithmA character string specifying the algorithm that was used to fit the model.
parametersA list containing the parameter settings that were used to fit the model that differ from the defaults.
allparametersA list containing all parameters used to fit the model.
modelA list containing the characteristics of the model returned by the algorithm.
- size
The number of points in each cluster.
- totss
Total sum of squared error to grand mean.
- withinss
A vector of within-cluster sum of squared error.
- tot_withinss
Total within-cluster sum of squared error.
- betweenss
Between-cluster sum of squared error.
h2o documentation built on May 29, 2024, 4:26 a.m.
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| H2OClusteringModel-class | R Documentation |
The H2OClusteringModel object.
Description
This virtual class represents a clustering model built by H2O.
Details
This object has slots for the key, which is a character string that points to the model key existing in the H2O cluster, the data used to build the model (an object of class H2OFrame).
Slots
model_idA
characterstring specifying the key for the model fit in the H2O cluster's key-value store.algorithmA
characterstring specifying the algorithm that was used to fit the model.parametersA
listcontaining the parameter settings that were used to fit the model that differ from the defaults.allparametersA
listcontaining all parameters used to fit the model.modelA
listcontaining the characteristics of the model returned by the algorithm.- size
The number of points in each cluster.
- totss
Total sum of squared error to grand mean.
- withinss
A vector of within-cluster sum of squared error.
- tot_withinss
Total within-cluster sum of squared error.
- betweenss
Between-cluster sum of squared error.
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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