Spark ML – Transform, fit, and predict methods (ml_ interface)
R/ml_transformation_methods.R
ml-transform-methods
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, ...)
## S3 method for class 'ml_model_classification'
ml_predict(x, dataset, probability_prefix = "probability_", ...) Arguments
| Arguments | 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.