Spark ML – Transform, fit, and predict methods (ml_ interface)
Methods for transformation, fit, and prediction. These are mirrors of the corresponding sdf-transform-methods.
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_", ...)
x |
A |
dataset |
A |
... |
Optional arguments; currently unused. |
probability_prefix |
String used to prepend the class probability output columns. |
These methods are
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.
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