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6.8. Pairwise metrics, Affinities and Kernels —...
b ) >= 0 , for all a and b 2. d ( a , b ) == 0 , if and...only if a = b , positive definiteness 3. d ( a , b ) == d ( b ,...scikit-learn.org/stable/modules/metrics.html -
cross_val_predict — scikit-learn 1.6.1 document...
y = None , * , groups = None , cv = None , n_jobs = None ,..., verbose = 0 , params = None , pre_dispatch = '2*n_jobs' , method...scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_predict.html -
Gaussian process classification (GPC) on iris d...
y = np . array ( iris . target , dtype = int ) h = 0.02 #...play with iris = datasets . load_iris () X = iris . data [:,...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_iris.html -
SVM with custom kernel — scikit-learn 1.6.1 doc...
cmap = plt . cm . Paired , ax = ax , response_method = "predict"...1 ], c = Y , cmap = plt . cm . Paired , edgecolors = "k" ) plt...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
StackingRegressor — scikit-learn 1.6.1 document...
final_estimator = None , * , cv = None , n_jobs = None , passthrough = False..., y = load_diabetes ( return_X_y = True ) >>> estimators = [ ......scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html -
SimpleImputer — scikit-learn 1.6.1 documentation
missing_values = nan , strategy = 'mean' , fill_value = None , copy = True...numerical value, default=None When strategy == “constant”, fill_value...scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html -
Recognizing hand-written digits — scikit-learn ...
axes = plt . subplots ( nrows = 1 , ncols = 4 , figsize = ( 10...subplots ( nrows = 1 , ncols = 4 , figsize = ( 10 , 3 )) for ax ,...scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html -
Fitting an Elastic Net with a precomputed Gram ...
y = make_regression ( n_samples = n_samples , noise = 0.5 ,...random_state = rng ) sample_weight = rng . lognormal ( size = n_samples...scikit-learn.org/stable/auto_examples/linear_model/plot_elastic_net_precomputed_gram_matrix_with_... -
StackingClassifier — scikit-learn 1.6.1 documen...
final_estimator = None , * , cv = None , stack_method = 'auto' , n_jobs...n_jobs = None , passthrough = False , verbose = 0 ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html -
orthogonal_mp_gram — scikit-learn 1.6.1 documen...
n_nonzero_coefs = None , tol = None , norms_squared = None , copy_Gram...copy_Gram = True , copy_Xy = True , return_path = False , return_n_iter...scikit-learn.org/stable/modules/generated/sklearn.linear_model.orthogonal_mp_gram.html