ml_model

The name of the machine learning routine used in the
encompassing model. Note that the model name generated will be
generated as <code>ml_model_<class></class></code>; that is, <code>ml_model</code>
will be prefixed.

class

model

Additional model information; typically supplied as named
values.

The R call used in generating this model object (ie,
the top-level R routine that wraps over the associated Spark ML
routine). Typically used for print output in e.g. <code>print</code>
and <code>summary</code> methods.

.call

Create an ML model object, wrapping the result of a Spark ML routine call.
The generated object will be an R list with S3 classes
<code>c("ml_model_<class>", "ml_model")</class></code>.

Provision, connect and interface to Apache Spark from within R.
This package supports connecting to local and remote Apache Spark clusters,
provides a dplyr-compatible back-end, and provides an interface to Spark's
built-in machine learning algorithms.

Javier Luraschi

sparklyr

R Interface to Apache Spark

ml_model function

The name of the machine learning routine used in the
encompassing model. Note that the model name generated will be
generated as <code>ml_model_<class></code>; that is, <code>ml_model</code>
will be prefixed.

Create an ML model object, wrapping the result of a Spark ML routine call.
The generated object will be an R list with S3 classes
<code>c("ml_model_<class>", "ml_model")</code>.

ml_model: Create an ML Model Object

Description

Usage

Arguments