ml-transform-methods

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, …)

ml_transform(x, dataset, …)

ml_fit_and_transform(x, dataset, …)

ml_predict(x, dataset, …)

ml_predictml_model_classification(x, dataset, probability_prefix = “probability_”, …)

Arguments

Argument	Description
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.