- Sort Score
- Num 10 results
- Language All
- Labels All
Results 231 - 240 of over 10,000 for 1 (0.12 seconds)
Filter
-
check_X_y — scikit-learn 1.8.0 documentation
ensure_min_samples = 1 , ensure_min_features = 1 , y_numeric = False...>>> X = [[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]] >>> y = [ 1 , 2 , 3 ]...scikit-learn.org/stable/modules/generated/sklearn.utils.check_X_y.html -
make_column_selector — scikit-learn 1.8.0 docum...
1. , 0. , 0. ], [-1.50755672, 1. , 0. , 0. ], [-0.30151134,...[-0.30151134, 0. , 1. , 0. ], [ 0.90453403, 0. , 0. , 1. ]]) __call__...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_selector.html -
non_negative_factorization — scikit-learn 1.8.0...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...version 1.4: Added 'auto' value. Changed in version 1.6: Default...scikit-learn.org/stable/modules/generated/sklearn.decomposition.non_negative_factorization.html -
MultiTaskElasticNetCV — scikit-learn 1.8.0 docu...
[ 1 , 1 ], [ 2 , 2 ]], ... [[ 0 , 0 ], [ 1 , 1 ], [ 2 ,...with 0 < l1_ratio <= 1. For l1_ratio = 1 the penalty is an L1/L2...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskElasticNetCV.html -
lars_path_gram — scikit-learn 1.8.0 documentation
the case method=’lasso’ is: ( 1 / ( 2 * n_samples )) * || y -...equation (see discussion in [1] ). Read more in the User Guide...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path_gram.html -
GaussianNB — scikit-learn 1.8.0 documentation
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> Y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
LatentDirichletAllocation — scikit-learn 1.8.0 ...
evaluate_every = -1 , total_samples = 1000000.0 , perp_tol = 0.1 , mean_change_tol...None, defaults to 1 / n_components . In [1] , this is called...scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html -
TfidfVectorizer — scikit-learn 1.8.0 documentation
ngram_range=(1 , 1) , max_df=1.0 , min_df=1 , max_features=None...ngram_range of (1, 1) means only unigrams, (1, 2) means unigrams...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html -
StandardScaler — scikit-learn 1.8.0 documentation
( data )) [[-1. -1.] [-1. -1.] [ 1. 1.] [ 1. 1.]] >>> print (...0 , 0 ], [ 0 , 0 ], [ 1 , 1 ], [ 1 , 1 ]] >>> scaler = StandardScaler...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html -
mutual_info_regression — scikit-learn 1.8.0 doc...
means 1 unless in a joblib.parallel_backend context. -1 means...References [ 1 ] Mutual Information on Wikipedia. [ 2 ] ( 1 , 2 ) A....scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_regression.html