H2OInfogram-class

H2OInfogram class contains a subset of what a normal H2OModel will return

R interface for 'H2O', the scalable open source machine learning
platform that offers parallelized implementations of many supervised and
unsupervised machine learning algorithms such as Generalized Linear
Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes,
Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection,
Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).

Tomas Fryda

R Interface for the 'H2O' Scalable Machine Learning Platform

Erin LeDell

Navdeep Gill

Spencer Aiello

Anqi Fu

Arno Candel

Cliff Click

Tom Kraljevic

Tomas Nykodym

Patrick Aboyoun

Michal Kurka

Michal Malohlava

Sebastien Poirier

Wendy Wong

Ludi Rehak

Eric Eckstrand

Brandon Hill

Sebastian Vidrio

Surekha Jadhawani

Amy Wang

Raymond Peck

Jan Gorecki

Matt Dowle

Yuan Tang

Lauren DiPerna

Veronika Maurerova

Yuliia Syzon

Adam Valenta

Marek Novotny

H2O.ai 

H2OInfogram-class function

<dl>
<dt><code>model_id</code></dt>
<dd>string returned as part of every <code>H2OModel</code></dd></dl>
<dt><code>algorithm</code></dt>
<dd>string denoting the algorithm used to build infogram</dd>
<dt><code>admissible_features</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold</dd>
<dt><code>admissible_features_valid</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold from validation frame</dd>
<dt><code>admissible_features_xval</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold from cv holdout set</dd>
<dt><code>net_information_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>
<dt><code>total_information_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>
<dt><code>safety_index_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>
<dt><code>relevance_index_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>
<dt><code>admissible_score</code></dt>
<dd><code>H2OFrame</code> that contains columns, admissible, admissible_index, relevance, cmi, cmi_raw</dd>
<dt><code>admissible_score_valid</code></dt>
<dd><code>H2OFrame</code> that contains columns, admissible, admissible_index, relevance, cmi, cmi_raw from validation frame</dd>
<dt><code>admissible_score_xval</code></dt>
<dd><code>H2OFrame</code> that contains averages of columns, admissible, admissible_index, relevance, cmi, cmi_raw from cv hold-out</dd>

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H2OInfogram class — H2OInfogram-class

<dl>
<dt><code>model_id</code></dt>
<dd>string returned as part of every <code>H2OModel</code></dd>


<dt><code>algorithm</code></dt>
<dd>string denoting the algorithm used to build infogram</dd>


<dt><code>admissible_features</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold</dd>


<dt><code>admissible_features_valid</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold from validation frame</dd>


<dt><code>admissible_features_xval</code></dt>
<dd>string array denoting all predictor names which pass the cmi and relelvance threshold from cv holdout set</dd>


<dt><code>net_information_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>


<dt><code>total_information_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>


<dt><code>safety_index_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>


<dt><code>relevance_index_threshold</code></dt>
<dd>numeric value denoting threshold used for predictor selection</dd>


<dt><code>admissible_score</code></dt>
<dd><code>H2OFrame</code> that contains columns, admissible, admissible_index, relevance, cmi, cmi_raw</dd>


<dt><code>admissible_score_valid</code></dt>
<dd><code>H2OFrame</code> that contains columns, admissible, admissible_index, relevance, cmi, cmi_raw from validation frame</dd>


<dt><code>admissible_score_xval</code></dt>
<dd><code>H2OFrame</code> that contains averages of columns, admissible, admissible_index, relevance, cmi, cmi_raw from cv hold-out</dd>


</dl>

H2OInfogram class

H2OInfogram-class: H2OInfogram class

Description

Arguments

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