evalml.automl.AutoMLSearch

class evalml.automl.AutoMLSearch(X_train=None, y_train=None, problem_type=None, objective='auto', max_iterations=None, max_time=None, patience=None, tolerance=None, data_splitter=None, allowed_pipelines=None, allowed_model_families=None, start_iteration_callback=None, add_result_callback=None, error_callback=None, additional_objectives=None, random_state=0, n_jobs=- 1, tuner_class=None, verbose=True, optimize_thresholds=False, ensembling=False, max_batches=None, problem_configuration=None, train_best_pipeline=True, _pipelines_per_batch=5)[source]

Automated Pipeline search.

Methods

__init__

Automated pipeline search

add_to_rankings

Fits and evaluates a given pipeline then adds the results to the automl rankings with the requirement that automl search has been run.

describe_pipeline

Describe a pipeline

get_pipeline

Given the ID of a pipeline training result, returns an untrained instance of the specified pipeline initialized with the parameters used to train that pipeline during automl search.

load

Loads AutoML object at file path

save

Saves AutoML object at file path

search

Find the best pipeline for the data set.

Attributes

best_pipeline

Returns a trained instance of the best pipeline and parameters found during automl search.

data_check_results

If there are data checks, return any error messages that are found

full_rankings

Returns a pandas.DataFrame with scoring results from all pipelines searched

has_searched

Returns True if search has been ran and False if not

rankings

Returns a pandas.DataFrame with scoring results from the highest-scoring set of parameters used with each pipeline.

results

Class that allows access to a copy of the results from automl_search.

Class Inheritance

Inheritance diagram of AutoMLSearch