api_reference.rst

API Reference

evalml.demos

Demo Datasets

load_fraud load_wine load_breast_cancer load_diabetes

evalml.preprocessing

Preprocessing

Utilities to preprocess data before using evalml.

drop_nan_target_rows label_distribution load_data number_of_features split_data

evalml.automl

AutoML

AutoML Search Classes

AutoMLSearch

evalml.automl.automl_algorithm

AutoML Algorithm Classes

AutoMLAlgorithm IterativeAlgorithm

evalml.pipelines

Pipelines

Pipeline Base Classes

PipelineBase ClassificationPipeline BinaryClassificationPipeline MulticlassClassificationPipeline RegressionPipeline

Classification Pipelines

BaselineBinaryPipeline BaselineMulticlassPipeline ModeBaselineBinaryPipeline ModeBaselineMulticlassPipeline

Regression Pipelines

BaselineRegressionPipeline MeanBaselineRegressionPipeline

Pipeline Graph Utils

precision_recall_curve graph_precision_recall_curve roc_curve graph_roc_curve confusion_matrix normalize_confusion_matrix graph_confusion_matrix calculate_permutation_importance graph_permutation_importance

evalml.pipelines.utils

Pipeline Utils

make_pipeline

evalml.pipelines.components

Components

Component Base Classes

Components represent a step in a pipeline.

ComponentBase Transformer Estimator

evalml.pipelines.components.utils

Component Utils

allowed_model_families get_estimators

evalml.pipelines.components

Transformers

Transformers are components that take in data as input and output transformed data.

DropColumns SelectColumns OneHotEncoder PerColumnImputer Imputer SimpleImputer StandardScaler RFRegressorSelectFromModel RFClassifierSelectFromModel DropNullColumns DateTimeFeaturizer TextFeaturizer

Estimators

Classifiers

Classifiers are components that output a predicted class label.

CatBoostClassifier ElasticNetClassifier ExtraTreesClassifier RandomForestClassifier LogisticRegressionClassifier XGBoostClassifier BaselineClassifier

Regressors

Regressors are components that output a predicted target value.

CatBoostRegressor ElasticNetRegressor LinearRegressor ExtraTreesRegressor RandomForestRegressor XGBoostRegressor BaselineRegressor

evalml.pipelines.prediction_explanations

Prediction Explanations

explain_prediction explain_predictions explain_predictions_best_worst

evalml.objectives

Objective Functions

Objective Base Classes

ObjectiveBase BinaryClassificationObjective MulticlassClassificationObjective RegressionObjective

Domain-Specific Objectives

FraudCost LeadScoring

Classification Objectives

AccuracyBinary AccuracyMulticlass AUC AUCMacro AUCMicro AUCWeighted BalancedAccuracyBinary BalancedAccuracyMulticlass F1 F1Micro F1Macro F1Weighted LogLossBinary LogLossMulticlass MCCBinary MCCMulticlass Precision PrecisionMicro PrecisionMacro PrecisionWeighted Recall RecallMicro RecallMacro RecallWeighted

Regression Objectives

R2 MAE MSE MeanSquaredLogError MedianAE MaxError ExpVariance RootMeanSquaredError RootMeanSquaredLogError

evalml.problem_types

Problem Types

ProblemTypes

handle_problem_types

evalml.model_family

Model Family

ModelFamily

handle_model_family

evalml.tuners

Tuners

Tuner SKOptTuner GridSearchTuner RandomSearchTuner

evalml.data_checks

Data Checks

Data Check Classes

DataCheck InvalidTargetDataCheck HighlyNullDataCheck IDColumnsDataCheck LabelLeakageDataCheck OutliersDataCheck NoVarianceDataCheck

DataChecks DefaultDataChecks

Data Check Messages

DataCheckMessage DataCheckError DataCheckWarning

Data Check Message Types

DataCheckMessageType

evalml.utils

Utils

import_or_raise convert_to_seconds get_random_state get_random_seed