evalml.pipelines.BaselineBinaryPipeline

class evalml.pipelines.BaselineBinaryPipeline(parameters, random_seed=0)[source]

Baseline Pipeline for binary classification.

name = 'Baseline Classification Pipeline'
custom_name = 'Baseline Classification Pipeline'
summary = 'Baseline Classifier'
component_graph = ['Baseline Classifier']
problem_type = 'binary'
model_family = 'baseline'
hyperparameters = {'Baseline Classifier': {}}
custom_hyperparameters = None
default_parameters = {'Baseline Classifier': {'strategy': 'mode'}}

Instance attributes

classes_

Gets the class names for the problem.

feature_importance

Return importance associated with each feature.

linearized_component_graph

parameters

Returns parameter dictionary for this pipeline

threshold

Threshold used to make a prediction.

Methods:

__init__

Machine learning classification pipeline made out of transformers and a classifier.

can_tune_threshold_with_objective

Determine whether the threshold of a binary classification pipeline can be tuned.

clone

Constructs a new pipeline with the same components, parameters, and random state.

compute_estimator_features

Transforms the data by applying all pre-processing components.

create_objectives

describe

Outputs pipeline details including component parameters

fit

Build a classification model. For string and categorical targets, classes are sorted

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 importance

load

Loads pipeline at file path

optimize_threshold

Optimize the pipeline threshold given the objective to use.

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

Class Inheritance

Inheritance diagram of BaselineBinaryPipeline