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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, av..

linear_model.RidgeClassifierCV linear_model.RidgeClassifierCV 파라미터 alphasndarray of shape (n_alphas,), default=(0.1, 1.0, 10.0) fit_interceptbool, default=True normalizebool, default=False scoringstr, callable, default=None cvint, cross-validation generator or an iterable, default=None class_weightdict or ‘balanced’, default=None store_cv_valuesbool, default=False

linear_model.RidgeClassifier linear_model.RidgeClassifier 파라미터 alphafloat, default=1.0 fit_interceptbool, default=True normalizebool, default=False copy_Xbool, default=True max_iterint, default=None tolfloat, default=1e-3 class_weightdict or ‘balanced’, default=None solver{‘auto’, ‘svd’, ‘cholesky’, ‘lsqr’, ‘sparse_cg’, ‘sag’, ‘saga’, ‘lbfgs’}, default=’auto’ positivebool, default=False random_s..

linear_model.Perceptron linear_model.Perceptron 파라미터 penalty{‘l2’,’l1’,’elasticnet’}, default=None 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 The verbosity level. eta0float, default=1 n_jobsint, default=None random_stateint, RandomState instance, default=No..

linear_model.PassiveAggressiveClassifier 파라미터 linear_model.PassiveAggressiveClassifier 파라미터 Cfloat, default=1.0 fit_interceptbool, default=True max_iterint, default=1000 tolfloat or None, default=1e-3 early_stoppingbool, default=False validation_fractionfloat, default=0.1 n_iter_no_changeint, default=5 shufflebool, default=True verboseint, default=0 lossstr, default=”hinge” n_jobsint or None, de..

linear_model.LogisticRegressionCV 파라미터 linear_model.LogisticRegressionCV 파라미터 Csint or list of floats, default=10 fit_interceptbool, default=True cvint or cross-validation generator, default=None dualbool, default=False penalty{‘l1’, ‘l2’, ‘elasticnet’}, default=’l2’ scoringstr or callable, default=None solver{‘newton-cg’, ‘lbfgs’, ‘liblinear’, ‘sag’, ‘saga’}, default=’lbfgs’ tolfloat, default=1..

linear_model.LogisticRegression 파라미터 linear_model.LogisticRegression 파라미터 penalty{‘l1’, ‘l2’, ‘elasticnet’, ‘none’}, default=’l2’ dualbool, default=False tolfloat, default=1e-4 Cfloat, default=1.0 fit_interceptbool, default=True intercept_scalingfloat, default=1 class_weightdict or ‘balanced’, default=None random_stateint, RandomState instance, default=None solver{‘newton-cg’, ‘lbfgs’, ‘liblinea..

sklearn.kernel_ridge.KernelRidge 파라미터 sklearn.kernel_ridge.KernelRidge 파라미터 alphafloat or array-like of shape (n_targets,), default=1.0 kernelstr or callable, default=”linear” gammafloat, default=None degreefloat, default=3 coef0float, default=1 kernel_paramsmapping of str to any, default=None