evalml.pipelines.ENMulticlassPipeline

class evalml.pipelines.ENMulticlassPipeline(parameters, random_state=0)

Elastic Net Pipeline for multiclass classification problems

name = 'ENMulticlass Pipeline'

custom_name = None

summary = 'Elastic Net Classifier w/ One Hot Encoder + Simple Imputer'

component_graph = ['One Hot Encoder', 'Simple Imputer', 'Elastic Net Classifier']

problem_type = 'multiclass'

model_family = 'linear_model'

hyperparameters = {'Elastic Net Classifier': {'alpha': Real(low=0, high=1, prior='uniform', transform='identity'), 'l1_ratio': Real(low=0, high=1, prior='uniform', transform='identity')}, 'One Hot Encoder': {}, 'Simple Imputer': {'impute_strategy': ['mean', 'median', 'most_frequent']}}

custom_hyperparameters = None

Instance attributes

feature_importances	Return feature importances.
parameters	Returns parameter dictionary for this pipeline

Methods:

__init__	Machine learning pipeline made out of transformers and a estimator.
describe	Outputs pipeline details including component parameters
fit	Build a model
get_component	Returns component by name
graph	Generate an image representing the pipeline graph
graph_feature_importance	Generate a bar graph of the pipeline’s feature importances
load	Loads pipeline at file path
predict	Make predictions using selected features.
predict_proba	Make probability estimates for labels.
save	Saves pipeline at file path
score	Evaluate model performance on objectives