verticapy.machine_learning.vertica.pipeline.Pipeline#
- class verticapy.machine_learning.vertica.pipeline.Pipeline(steps: list, overwrite_model: bool = False)#
Creates a Pipeline object, which sequentially applies a list of transforms and a final estimator. The intermediate steps must implement a transform method.
Parameters#
- steps: list
List of (name, transform) tuples (implementing fit/transform) that are chained, in the order in which they are chained, where the last object is an estimator.
- overwrite_model: bool, optional
If set to True, training a model in the pipeline with the same name as an existing model overwrites the existing model.
- __init__(steps: list, overwrite_model: bool = False) None#
Methods
__init__(steps[, overwrite_model])drop()Drops the model from the Vertica database.
fit(input_relation, X[, y, test_relation, ...])Trains the model.
Returns the model's Parameters.
inverse_transform([vdf, X])Applies the inverse model transformation on a vDataFrame.
predict([vdf, X, name])Applies the model on a vDataFrame.
report()Computes a regression/classification report using multiple metrics to evaluate the model depending on its type.
score([metric])Computes the model score.
set_params([parameters])Sets the parameters of the model.
transform([vdf, X])Applies the model on a vDataFrame.