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sklearn.linear_model.SGDClassifier 파라미터<Python>/[Sklearn] 2022. 1. 8. 19:30728x90
linear_model.SGDClassifier
class sklearn.linear_model.SGDClassifier(loss='hinge', *, penalty='l2', alpha=0.0001, l1_ratio=0.15, fit_intercept=True, max_iter=1000, tol=0.001, 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)
linear_model.SGDClassifier 파라미터
lossstr, default=’hinge’
penalty{‘l2’, ‘l1’, ‘elasticnet’}, default=’l2’
alphafloat, default=0.0001
l1_ratiofloat, default=0.15
fit_interceptbool, default=True
max_iterint, default=1000
tolfloat, default=1e-3
shufflebool, default=True
verboseint, default=0
epsilonfloat, default=0.1
n_jobsint, default=None
random_stateint, RandomState instance, default=None
learning_ratestr, default=’optimal’
eta0float, default=0.0
power_tfloat, default=0.5
early_stoppingbool, default=False
validation_fractionfloat, default=0.1
n_iter_no_changeint, default=5
class_weightdict, {class_label: weight} or “balanced”, default=None
warm_startbool, default=False
averagebool or int, default=False
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