ml_pca

An object coercable to a Spark DataFrame (typically, a
<code>tbl_spark</code>).

The columns to use in the principal components
analysis. Defaults to all columns in <code>x</code>.

features

Optional arguments, used to affect the model generated. See
<code><a rd-options="" href="/link/ml_options?package=sparklyr&version=0.3.7" data-mini-rdoc="sparklyr::ml_options">ml_options</a></code> for more details.

ml.options


Perform principal components analysis on a Spark DataFrame.


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_pca function

Optional arguments, used to affect the model generated. See
<code><a rd-options='' href='ml_options'>ml_options</a></code> for more details.

ml_pca: Spark ML -- Principal Components Analysis

Description

Usage

Arguments

See Also