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RandomForestRegressor — scikit-learn 1.5.2 docu...
n_estimators = 100 , * , criterion = 'squared_error' , max_depth = None...min_weight_fraction_leaf = 0.0 , max_features = 1.0 , max_leaf_nodes = None , ...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html -
ExtraTreeClassifier — scikit-learn 1.5.2 docume...
criterion = 'gini' , splitter = 'random' , max_depth = None , min_samples_split...min_weight_fraction_leaf = 0.0 , max_features = 'sqrt' , random_state = None ,...scikit-learn.org/stable/modules/generated/sklearn.tree.ExtraTreeClassifier.html -
DictVectorizer — scikit-learn 1.5.2 documentation
dtype=<class 'numpy.float64'> , separator='=' , sparse=True ,...DictVectorizer >>> v = DictVectorizer ( sparse = False ) >>> D = [{ 'foo'...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html -
3.1. Cross-validation: evaluating estimator per...
kernel = 'linear' , C = 1 , random_state = 0 ) >>> scores = cross_validate...(60,)) >>> clf = svm . SVC ( kernel = 'linear' , C = 1 ) . fit (...scikit-learn.org/stable/modules/cross_validation.html -
StratifiedKFold — scikit-learn 1.5.2 documentation
n_splits = 5 , * , shuffle = False , random_state = None ) [source]...StratifiedKFold(n_splits=2, random_state=None, shuffle=False) >>> for i...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html -
LeaveOneGroupOut — scikit-learn 1.5.2 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 -
homogeneity_completeness_v_measure — scikit-lea...
beta = 1.0 ) [source] # Compute the homogeneity...evaluate. beta float, default=1.0 Ratio of weight attributed...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_completeness_v_measure.html -
名前付き区分値の自動生成(namedcls) | LastaFlute
map:{ code=[code]; name=[name]; alias=[alias]; comment=[comment]...map:{ code=[code]; name=[name]; alias=[alias]; comment=[comment]...dbflute.seasar.org/ja/lastaflute/howto/dbflute/namedcls.html -
LinearSVC — scikit-learn 1.5.2 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 -
Release Highlights for scikit-learn 1.0 — sciki...
n_iter_no_change = 10 , tol = 1e-7 , verbose = 0 , random_state = None ,...loss = "squared_error" , learning_rate = 0.1 , max_iter = 100...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html