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H2OClusteringModel-class

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_id

A character string specifying the key for the model fit in the H2O cluster's key-value store.

algorithm

A character string specifying the algorithm that was used to fit the model.

parameters

A list containing the parameter settings that were used to fit the model that differ from the defaults.

allparameters

A list containing all parameters used to fit the model.

model

A 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

R Interface for the 'H2O' Scalable Machine Learning Platform

v3.32.1.2
Apache License (== 2.0)
Authors
Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], Tomas Fryda [ctb], H2O.ai [cph, fnd]
Initial release
2021-04-29

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