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ConvergenceWarning — scikit-learn 1.8.0 documen...
convergence problems Changed in version 0.18: Moved from sklearn.utils....scikit-learn.org/stable/modules/generated/sklearn.exceptions.ConvergenceWarning.html -
TruncatedSVD — scikit-learn 1.8.0 documentation
explained_variance_ratio_ ) [0.0157 0.0512 0.0499 0.0479 0.0453] >>> print (...tol float, default=0.0 Tolerance for ARPACK. 0 means machine precision....scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html -
RFECV — scikit-learn 1.8.0 documentation
ranking_ array([1, 1, 1, 1, 1, 6, 4, 3, 2, 5]) For a detailed...each iteration. If within (0.0, 1.0), then step corresponds to...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html -
HashingVectorizer — scikit-learn 1.8.0 document...
ngram_range of (1, 1) means only unigrams, (1, 2) means unigrams...\\w\\w+\\b' , ngram_range=(1 , 1) , analyzer='word' , n_features=1048576...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.HashingVectorizer.html -
SelectFdr — scikit-learn 1.8.0 documentation
alpha=0.05 ) [source] # Filter: Select...all strings. Added in version 1.0. See also f_classif ANOVA F-value...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFdr.html -
SelectFwe — scikit-learn 1.8.0 documentation
alpha=0.05 ) [source] # Filter: Select...all strings. Added in version 1.0. See also f_classif ANOVA F-value...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFwe.html -
PairwiseKernel — scikit-learn 1.8.0 documentation
array([[0.8880, 0.05663, 0.05532], [0.8676, 0.07073, 0.06165]]) __call__...PairwiseKernel ( gamma = 1.0 , gamma_bounds = (1e-05, 100000.0) , metric =...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.PairwiseKernel.html -
dict_learning — scikit-learn 1.8.0 documentation
axis = 1 ) / np . sum ( X ** 2 , axis = 1 )) np.float64(0.0192)..., alpha , max_iter = 100 , tol = 1e-08 , method = 'lars' , n_jobs...scikit-learn.org/stable/modules/generated/sklearn.decomposition.dict_learning.html -
Product — scikit-learn 1.8.0 documentation
random_state = 0 ) . fit ( X , y ) >>> gpr . score ( X , y ) 1.0 >>> kernel...n_samples = 500 , noise = 0 , random_state = 0 ) >>> kernel = Product...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html -
Hyperparameter — scikit-learn 1.8.0 documentation
constant_value = 1.0 , ... constant_value_bounds = ( 0.0 , 10.0 )) We can...constant_value : 1.0 constant_value_bounds : (0.0, 10.0) bounds # Alias...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Hyperparameter.html