8000 [WIP] Add Generalized Linear Models (#9405) · lorentzenchr/scikit-learn@33e2892 · GitHub
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Christian Lorentzen
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[WIP] Add Generalized Linear Models (scikit-learn#9405)
* Fixed pep8 * Fixed flake8 * Rename GeneralizedLinearModel as GeneralizedLinearRegressor * Use of six.with_metaclass * PEP257: summary should be on same line as quotes * Docstring of class GeneralizedLinearRegressor: \ before mu * Arguments family and link accept strings * Use of ConvergenceWarning
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‎sklearn/linear_model/__init__.py

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lasso_path, enet_path, MultiTaskLasso,
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MultiTaskElasticNet, MultiTaskElasticNetCV,
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MultiTaskLassoCV)
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from .glm import (Link, IdentityLink, LogLink,
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ExponentialDispersionModel, TweedieDistribution,
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NormalDistribution, GaussianDistribution,
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PoissonDistribution, GammaDistribution,
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InverseGaussianDistribution, GeneralizedHyperbolicSecand,
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GeneralizedLinearModel)
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from .glm import (TweedieDistribution,
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GeneralizedLinearRegressor)
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from .huber import HuberRegressor
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from .sgd_fast import Hinge, Log, ModifiedHuber, SquaredLoss, Huber
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from .stochastic_gradient import SGDClassifier, SGDRegressor
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'BayesianRidge',
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'ElasticNet',
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'ElasticNetCV',
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'GeneralizedLinearModel',
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'Hinge',
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'Huber',
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'HuberRegressor',
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'orthogonal_mp',
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'orthogonal_mp_gram',
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'ridge_regression',
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'RANSACRegressor']
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'RANSACRegressor',
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'GeneralizedLinearRegressor',
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'TweedieDistribution']

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