H2OClusteringModel-class


This virtual class represents a clustering model built by H2O.


R scripting functionality for H2O, the open source
math engine for big data that computes parallel distributed
machine learning algorithms such as generalized linear models,
gradient boosting machines, random forests, and neural networks
(deep learning) within various cluster environments.

Tom Kraljevic

R Interface for H2O

H2OClusteringModel-class function

 <dl>
<dt><code>model_id</code></dt><dd>A <code>character</code> string specifying the key for the model fit in the H2O cloud's key-value store.</dd> <dt><code>algorithm</code></dt><dd>A <code>character</code> string specifying the algorithm that was used to fit the model.</dd> <dt><code>parameters</code></dt><dd>A <code>list</code> containing the parameter settings that were used to fit the model that differ from the defaults.</dd> <dt><code>allparameters</code></dt><dd>A <code>list</code> containing all parameters used to fit the model.</dd> <dt><code>model</code></dt><dd>A <code>list</code> containing the characteristics of the model returned by the algorithm.
<dl>
  <dt>size </dt><dd>The number of points in each cluster.</dd> <dt>totss </dt><dd>Total sum of squared error to grand mean.</dd> <dt>withinss </dt><dd>A vector of within-cluster sum of squared error.</dd> <dt>tot_withinss </dt><dd>Total within-cluster sum of squared error.</dd> <dt>betweenss </dt><dd>Between-cluster sum of squared error.</dd> </dl>
</dd> </dl>

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H2OClusteringModel-class: The H2OClusteringModel object.

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Arguments

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