Cardea
cardea.modeling.
Modeler
A class responsible for executing various Machine Learning Pipelines using MLBlocks.
__init__
Initialize self. See help(type(self)) for accurate signature.
Methods
__init__(pipeline, problem_type)
Initialize self.
evaluate(X, y[, test_size, shuffle, tune, …])
evaluate
Evaluate the pipelines.
fit(X, y[, tune, max_evals, scoring, verbose])
fit
Fit and select the pipelines.
fit_predict(X, y[, tune, max_evals, …])
fit_predict
Fit the pipeline and make predictions
k_fold_validation(hyperparameters, X, y[, …])
k_fold_validation
Score the pipeline through k-fold validation with the given scoring function.
load(path)
load
Load a Modeler object from a pickle file
predict(X)
predict
Predict the input data
save(path)
save
Save the object in a pickle file.
test(X, y[, scoring])
test
Test the trained pipeline.
train_test_split(X, y[, test_size, shuffle])
train_test_split
Split the training dataset and the testing dataset.
tune(X, y[, max_evals, scoring, verbose])
tune
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.