cardea.modeling.Modeler

class cardea.modeling.Modeler(pipeline, problem_type)

A class responsible for executing various Machine Learning Pipelines using MLBlocks.

__init__(pipeline, problem_type)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(pipeline, problem_type)	Initialize self.
evaluate(X, y[, test_size, shuffle, tune, …])	Evaluate the pipelines.
fit(X, y[, tune, max_evals, scoring, verbose])	Fit and select the pipelines.
fit_predict(X, y[, tune, max_evals, …])	Fit the pipeline and make predictions
k_fold_validation(hyperparameters, X, y[, …])	Score the pipeline through k-fold validation with the given scoring function.
load(path)	Load a Modeler object from a pickle file
predict(X)	Predict the input data
save(path)	Save the object in a pickle file.
test(X, y[, scoring])	Test the trained pipeline.
train_test_split(X, y[, test_size, shuffle])	Split the training dataset and the testing dataset.
tune(X, y[, max_evals, scoring, verbose])	Tune the pipeline hyper-parameters and select the optimized model.

Attributes

classification_metrics	Supported classification metrics functions.
pipeline	Pipeline.
regression_metrics	Supported regression metrics functions.
target_metrics	Supported metrics functions for the given problem type.

cardea.modeling cardea.modeling.Modeler.train_test_split