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load_breast_cancer — scikit-learn 1.7.2 documen...
load_breast_cancer () >>> data . target [[ 10 , 50 , 85 ]] array([0, 1, 0]) >>>...list ( data . target_names ) [np.str_('malignant'), np.str_('benign')]...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html -
set_config — scikit-learn 1.7.2 documentation
print ‘SVC(C=1.0, cache_size=200, …)’ with all the non-changed...to True. display {‘text’, ‘diagram’}, default=None If ‘diagram’,...scikit-learn.org/stable/modules/generated/sklearn.set_config.html -
MLPRegressor — scikit-learn 1.7.2 documentation
function, returns f(x) = 1 / (1 + exp(-x)). ‘tanh’, the hyperbolic tan...function, returns f(x) = max(0, x) solver {‘lbfgs’, ‘sgd’, ‘adam’},...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html -
plot_release_highlights_1_7_0.zip
# %% # Array API support # ---------- # Several functions have...Pipeline([("sc", StandardScaler()), ("clf", clf)], transform_input=["X_val"])...scikit-learn.org/stable/_downloads/0f052545c78541815099d62501f25a9e/plot_release_highlights_1_7_0... -
plot_release_highlights_1_7_0.ipynb
Pipeline([(\"sc\", StandardScaler()), (\"clf\", clf)], transf...0))\nmodel" ] }, { "cell_type": "markdown", "metadata": {}, "source":...scikit-learn.org/stable/_downloads/b7d178d09f44d400894015228deb0ddb/plot_release_highlights_1_7_0... -
EllipticEnvelope — scikit-learn 1.7.2 documenta...
([[ 0 , 0 ], ... [ 3 , 3 ]]) array([ 1, -1]) >>> cov . covariance_...np . array ([[ .8 , .3 ], ... [ .3 , .4 ]]) >>> X = np . random...scikit-learn.org/stable/modules/generated/sklearn.covariance.EllipticEnvelope.html -
ShrunkCovariance — scikit-learn 1.7.2 documenta...
covariance_ array([[0.7387, 0.2536], [0.2536, 0.4110]]) >>> cov . location_...sqrt(tr(A^t.A)) - ‘spectral’: sqrt(max(eigenvalues(A^t.A)) where...scikit-learn.org/stable/modules/generated/sklearn.covariance.ShrunkCovariance.html -
CalibrationDisplay — scikit-learn 1.7.2 documen...
CalibrationDisplay ( prob_true , prob_pred , y_prob ) >>> disp . plot () <...>...from_estimator ( estimator , X , y , * , n_bins = 5 , strategy = 'uniform'...scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibrationDisplay.html -
MeanShift — scikit-learn 1.7.2 documentation
= np . array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ],...= 2 ) . fit ( X ) >>> clustering . labels_ array([1, 1, 1, 0,...scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html -
fetch_kddcup99 — scikit-learn 1.7.2 documentation
Guide . Added in version 0.18. Parameters : subset {‘SA’, ‘SF’,...encountered. Added in version 1.5. delay float, default=1.0 Number...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_kddcup99.html