- Sort Score
- Num 10 results
- Language All
- Labels All
Results 2281 - 2290 of over 10,000 for * (5.46 seconds)
Filter
-
power_transform — scikit-learn 1.8.0 documentation
'box-cox' )) [[-1.332 -0.707] [ 0.256 -0.707] [ 1.076 1.414]] Warning...Available methods are: ‘yeo-johnson’ [1] , works with positive and negative...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.power_transform.html -
RobustScaler — scikit-learn 1.8.0 documentation
array([[ 0. , -2. , 0. ], [-1. , 0. , 0.4], [ 1. , 0. , -1.6]]) fit...q_max), 0.0 < q_min < q_max < 100.0, default=(25.0, 75.0) Quantile...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html -
Normalizer — scikit-learn 1.8.0 documentation
array([[0.8, 0.2, 0.4, 0.4], [0.1, 0.3, 0.9, 0.3], [0.5, 0.7, 0.5,...all strings. Added in version 1.0. See also normalize Equivalent...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Normalizer.html -
QuantileTransformer — scikit-learn 1.8.0 docume...
scale = 0.25 , size = ( 25 , 1 )), axis = 0 ) >>> qt = QuantileTransformer...version 0.19. Parameters : n_quantiles int, default=1000 or n_samples...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
binarize — scikit-learn 1.8.0 documentation
binarize >>> X = [[ 0.4 , 0.6 , 0.5 ], [ 0.6 , 0.1 , 0.2 ]] >>> binarize...threshold = 0.5 ) array([[0., 1., 0.], [1., 0., 0.]]) On this...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.binarize.html -
KNeighborsTransformer — scikit-learn 1.8.0 docu...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) set_output...to [1,1,1] >>> samples = [[ 0. , 0. , 0. ], [ 0. , .5 , 0. ],...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html -
MLPRegressor — scikit-learn 1.8.0 documentation
validation_fraction = 0.1 , beta_1 = 0.9 , beta_2 = 0.999 , epsilon = 1e-08 , n_iter_no_change...learning_rate_init = 0.001 , power_t = 0.5 , max_iter = 200 ,...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html -
ClassifierTags — scikit-learn 1.8.0 documentation
accuracy of 0.83 on make_blobs(n_samples=300, random_state=0) . The...scikit-learn.org/stable/modules/generated/sklearn.utils.ClassifierTags.html -
OneClassSVM — scikit-learn 1.8.0 documentation
coef0 = 0.0 , tol = 0.001 , nu = 0.5 , shrinking = True...>>> X = [[ 0 ], [ 0.44 ], [ 0.45 ], [ 0.46 ], [ 1 ]] >>> clf...scikit-learn.org/stable/modules/generated/sklearn.svm.OneClassSVM.html -
Binarizer — scikit-learn 1.8.0 documentation
X ) array([[1., 0., 1.], [1., 0., 0.], [0., 1., 0.]]) fit ( X...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Binarizer.html