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KFold — scikit-learn 1.7.2 documentation
n_splits = 5 , * , shuffle = False , random_state = None ) [source]...KFold(n_splits=2, random_state=None, shuffle=False) >>> for i...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
AdditiveChi2Sampler — scikit-learn 1.7.2 docume...
y = load_digits ( return_X_y = True ) >>> chi2sampler = AdditiveChi2Sampler...>>> clf = SGDClassifier ( max_iter = 5 , random_state = 0 , tol...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.AdditiveChi2Sampler.html -
QuantileTransformer — scikit-learn 1.7.2 docume...
( loc = 0.5 , scale = 0.25 , size = ( 25 , 1 )), axis = 0 ) >>>...ignore_implicit_zeros = False , subsample = 10000 , random_state = None , copy...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
GaussianProcessClassifier — scikit-learn 1.7.2 ...
n_restarts_optimizer = 0 , max_iter_predict = 100 , warm_start = False , copy_X_train...copy_X_train = True , random_state = None , multi_class = 'one_vs_rest'...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html -
QuantileRegressor — scikit-learn 1.7.2 document...
quantile = 0.5 , alpha = 1.0 , fit_intercept = True , solver = 'highs'...n_samples , n_features = 10 , 2 >>> rng = np . random . RandomState...scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html -
InputTags — scikit-learn 1.7.2 documentation
bool = False , sparse : bool = False , categorical : bool = False...bool = False , dict : bool = False , positive_only : bool = False...scikit-learn.org/stable/modules/generated/sklearn.utils.InputTags.html -
Probabilistic predictions with Gaussian process...
train_size = 50 rng = np . random . RandomState ( 0 ) X = rng . uniform...train_size ], c = "k" , label = "Train data" , edgecolors = ( 0 , 0 ,...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html -
Matern — scikit-learn 1.7.2 documentation
length_scale = 1.0 , length_scale_bounds = (1e-05, 100000.0) , nu = 1.5...>>> X , y = load_iris ( return_X_y = True ) >>> kernel = 1.0 * Matern...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Matern.html -
CategoricalNB — scikit-learn 1.7.2 documentation
alpha = 1.0 , force_alpha = True , fit_prior = True , class_prior...class_prior = None , min_categories = None ) [source] # Naive Bayes...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.CategoricalNB.html -
Factor Analysis (with rotation) to visualize pa...
cmap = "RdBu_r" , vmin =- 1 , vmax = 1 ) ax . set_xticks...ncols = len ( methods ), figsize = ( 10 , 8 ), sharey = True )...scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html