h2o.varimp

<p>An <a href="/link/?package=h2o&version=3.22.1.1" h2omodel'="" data-mini-rdoc="h2o::"></a>'>H2OModel object.</p>

object

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, Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox
Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic
machine learning algorithm (AutoML).

Erin LeDell

R Interface for 'H2O'

Navdeep Gill

Spencer Aiello

Anqi Fu

Arno Candel

Cliff Click

Tom Kraljevic

Tomas Nykodym

Patrick Aboyoun

Michal Kurka

Michal Malohlava

Ludi Rehak

Eric Eckstrand

Brandon Hill

Sebastian Vidrio

Surekha Jadhawani

Amy Wang

Raymond Peck

Wendy Wong

Jan Gorecki

Matt Dowle

Yuan Tang

Lauren DiPerna

H2O.ai 

h2o.varimp function

<p>An <a href='<a href='H2OModel'></a>'>H2OModel</a> object.</p>

Retrieve the variable importance. — h2o.varimp

Retrieve the variable importance.

h2o.varimp: Retrieve the variable importance.

Description

Usage

Arguments