simpleml.models.classifiers.sklearn.linear_model module

Wrapper module around sklearn.linear_model

class simpleml.models.classifiers.sklearn.linear_model.SklearnLogisticRegression(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.SklearnLogisticRegressionCV(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.SklearnPerceptron(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.SklearnRidgeClassifier(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.SklearnRidgeClassifierCV(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.SklearnSGDClassifier(has_external_files=True, external_model_kwargs={}, params={}, **kwargs)

Bases: simpleml.models.classifiers.sklearn.base_sklearn_classifier.SklearnClassifier

author

created_timestamp

feature_metadata

filepaths

has_external_files

hash_

id

metadata_

modified_timestamp

name

params

pipeline

pipeline_id

project

registered_name

version

version_description

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnLogisticRegression(penalty='l2', dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=None, random_state=None, solver='warn', max_iter=100, multi_class='warn', verbose=0, warm_start=False, n_jobs=None)

Bases: sklearn.linear_model.logistic.LogisticRegression, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnLogisticRegressionCV(Cs=10, fit_intercept=True, cv='warn', dual=False, penalty='l2', scoring=None, solver='lbfgs', tol=0.0001, max_iter=100, class_weight=None, n_jobs=None, verbose=0, refit=True, intercept_scaling=1.0, multi_class='warn', random_state=None)

Bases: sklearn.linear_model.logistic.LogisticRegressionCV, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnPerceptron(penalty=None, alpha=0.0001, fit_intercept=True, max_iter=None, tol=None, shuffle=True, verbose=0, eta0=1.0, n_jobs=None, random_state=0, early_stopping=False, validation_fraction=0.1, n_iter_no_change=5, class_weight=None, warm_start=False, n_iter=None)

Bases: sklearn.linear_model.perceptron.Perceptron, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnRidgeClassifier(alpha=1.0, fit_intercept=True, normalize=False, copy_X=True, max_iter=None, tol=0.001, class_weight=None, solver='auto', random_state=None)

Bases: sklearn.linear_model.ridge.RidgeClassifier, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnRidgeClassifierCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize=False, scoring=None, cv=None, class_weight=None, store_cv_values=False)

Bases: sklearn.linear_model.ridge.RidgeClassifierCV, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented

class simpleml.models.classifiers.sklearn.linear_model.WrappedSklearnSGDClassifier(loss='hinge', penalty='l2', alpha=0.0001, l1_ratio=0.15, fit_intercept=True, max_iter=None, tol=None, shuffle=True, verbose=0, epsilon=0.1, n_jobs=None, random_state=None, learning_rate='optimal', eta0=0.0, power_t=0.5, early_stopping=False, validation_fraction=0.1, n_iter_no_change=5, class_weight=None, warm_start=False, average=False, n_iter=None)

Bases: sklearn.linear_model.stochastic_gradient.SGDClassifier, simpleml.models.classifiers.external_models.ClassificationExternalModelMixin

get_feature_metadata(features, **kwargs)

By default nothing is implemented