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year=2016, month=2, day=16, hour=23, minute=38, second=10 8 8...year=2016, month=2, day=16, hour=23, minute=38, second=10 red=255,...www.elastic.co/android-chrome-192x192.png -
plot_classifier_comparison.py
""" ========== Classifier comparison ========== A comparison...random_state=42), SVC(gamma=2, C=1, random_state=42), GaussianProcessClass(1.0...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
Comparing different hierarchical linkage method...
selection X = StandardScaler () . fit_transform ( X ) # ========== # Create...Create cluster objects # ========== ward = cluster . AgglomerativeCluster...scikit-learn.org/stable/auto_examples/cluster/plot_linkage_comparison.html -
Faces dataset decompositions — scikit-learn 1.6...
_ = fetch_olivetti_faces ( return_X_y = True , shuffle = True...n_col = 2 , 3 n_components = n_row * n_col image_shape = ( 64...scikit-learn.org/stable/auto_examples/decomposition/plot_faces_decomposition.html -
Tweedie regression on insurance claims — scikit...
y_label = None , title = None , ax = None , fill_legend = False..."ClaimAmount" ] == 0 ) & ( df [ "ClaimNb" ] >= 1 ), "ClaimNb" ] = 0 log_scale_transformer...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
Label Propagation learning a complex structure ...
labels == outer , 1 ], color = "navy" , marker = "s" , lw = 0 ,...labels == inner , 0 ], X [ labels == inner , 1 ], color = "c" ,...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_structure.html -
Demo of OPTICS clustering algorithm — scikit-le...
( colors ): Xk = space [ labels == klass ] Rk = reachability [...space [ labels == - 1 ], reachability [ labels == - 1 ], "k." ,...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
Permutation Importance vs Random Forest Feature...
n_repeats = 10 , random_state = 42 , n_jobs = 2 ) test_results = pe..., y = fetch_openml ( "titanic" , version = 1 , as_frame = True...scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance.html -
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Release Highlights for scikit-learn 1.1 — sciki...
random_state = 0 ) km = KMeans ( n_clusters = 5 , random_state = 0 , n_init...10 , num = 2000 ) X = X_1d . reshape ( - 1 , 1 ) y = X_1d * np...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_1_0.html
