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LinearSVC — scikit-learn 1.7.0 documentation
penalty = 'l2' , loss = 'squared_hinge' , * , dual = 'auto' ,..., tol = 0.0001 , C = 1.0 , multi_class = 'ovr' , fit_intercept...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
RANSACRegressor — scikit-learn 1.7.0 documentation
estimator = None , * , min_samples = None , residual_threshold = None...is_data_valid = None , is_model_valid = None , max_trials = 100 , max_skips...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RANSACRegressor.html -
Sample pipeline for text feature extraction and...
data_train = fetch_20newsgroups ( subset = "train" , categories = categories...categories , shuffle = True , random_state = 42 , remove = ( "headers"...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_text_feature_extraction.html -
OrScopeQuery | DBFlute
MEMBER_STATUS_CODE = 'WDL' or (dfloc.MEMBER_ID >= 100 and dfloc.FORMALIZED_DATETIME...where (dfloc.MEMBER_ID = 1 or dfloc.MEMBER_ID = 3 ) 但し、同カラムに対する同じ...dbflute.seasar.org/ja/manual/function/ormapper/conditionbean/query/orscopequery.html -
LeaveOneGroupOut — scikit-learn 1.7.0 documenta...
Train: index=[2 3], group=[2 2] Test: index=[0 1], group=[1 1] Fold...Train: index=[0 1], group=[1 1] Test: index=[2 3], group=[2 2] get_metadata_routing...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeaveOneGroupOut.html -
NuSVC — scikit-learn 1.7.0 documentation
nu = 0.5 , kernel = 'rbf' , degree = 3 , gamma = 'scale'...coef0 = 0.0 , shrinking = True , probability = False , tol = 0.001...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html -
SelectFromModel — scikit-learn 1.7.0 documentation
threshold = None , prefit = False , norm_order = 1 , max_features...max_features = None , importance_getter = 'auto' ) [source] # Meta-transformer...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFromModel.html -
BaggingClassifier — scikit-learn 1.7.0 document...
special cases with k == 1 , otherwise k==n_classes . fit ( X ,...estimator = None , n_estimators = 10 , * , max_samples = 1.0 , max_features...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html -
Fitting an Elastic Net with a precomputed Gram ...
y = make_regression ( n_samples = n_samples , noise = 0.5 ,...random_state = rng ) sample_weight = rng . lognormal ( size = n_samples...scikit-learn.org/stable/auto_examples/linear_model/plot_elastic_net_precomputed_gram_matrix_with_... -
config_context — scikit-learn 1.7.0 documentation
assume_finite = None , working_memory = None , print_changed_only = None...None , display = None , pairwise_dist_chunk_size = None , enabl...scikit-learn.org/stable/modules/generated/sklearn.config_context.html