ml-transform-methods: Spark ML - Transform, fit, and predict methods (ml_...

In rstudio/sparklyr: R Interface to Apache Spark

Spark ML – Transform, fit, and predict methods (ml_ interface)

Description

Methods for transformation, fit, and prediction. These are mirrors of the corresponding sdf-transform-methods.

Usage

is_ml_transformer(x)

is_ml_estimator(x)

ml_fit(x, dataset, ...)

## Default S3 method:
ml_fit(x, dataset, ...)

ml_transform(x, dataset, ...)

ml_fit_and_transform(x, dataset, ...)

ml_predict(x, dataset, ...)

## S3 method for class 'ml_model_classification'
ml_predict(x, dataset, probability_prefix = "probability_", ...)

Arguments

x	A ml_estimator, ml_transformer (or a list thereof), or ml_model object.
dataset	A tbl_spark.
...	Optional arguments; currently unused.
probability_prefix	String used to prepend the class probability output columns.

Details

These methods are

Value

When x is an estimator, ml_fit() returns a transformer whereas ml_fit_and_transform() returns a transformed dataset. When x is a transformer, ml_transform() and ml_predict() return a transformed dataset. When ml_predict() is called on a ml_model object, additional columns (e.g. probabilities in case of classification models) are appended to the transformed output for the user's convenience.

rstudio/sparklyr documentation built on Sept. 18, 2024, 6:10 a.m.