ml-transform-methods

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

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, ...)

# S3 method for 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.

Aliases
  • ml-transform-methods
  • is_ml_transformer
  • is_ml_estimator
  • ml_fit
  • ml_transform
  • ml_fit_and_transform
  • ml_predict
  • ml_predict.ml_model_classification
Documentation reproduced from package sparklyr, version 0.9.4, License: Apache License 2.0 | file LICENSE

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