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2.8. Density Estimation — scikit-learn 1.6.1 do...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...\(x_i; i=1\cdots N\) is given by: \[\rho_K(y) = \sum_{i=1}^{N} K(y...scikit-learn.org/stable/modules/density.html -
A demo of the mean-shift clustering algorithm —...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , _ = make_blobs...matplotlib.pyplot as plt plt . figure ( 1 ) plt . clf () colors = [ "#dede00"...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
8. Computing with scikit-learn — scikit-learn 1...
1.1. Scaling with instances using out-of-core...Computing with scikit-learn # 8.1. Strategies to scale computationally:...scikit-learn.org/stable/computing.html -
Imputing missing values before building an esti...
mses_california [ 1 ], stds_california [ 1 ] = get_impute_zero_score...y_miss_california ) mses_diabetes [ 1 ], stds_diabetes [ 1 ] = get_impute_zero_score...scikit-learn.org/stable/auto_examples/impute/plot_missing_values.html -
Ordinary Least Squares and Ridge Regression Var...
1 ] . T y_train = [ 0.5 , 1 ] X_test = np . c_...this_X = 0.1 * np . random . normal ( size = ( 2 , 1 )) + X_train...scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge_variance.html -
L1-based models for Sparse Signals — scikit-lea...
1 , n_samples ) y += 0.2 * rng . normal ( 0 , 1 , n_samples...linthresh = 10e-4 , vmin =- 1 , vmax = 1 ), cbar_kws = { "label"...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
Model-based and sequential feature selection — ...
027 1.058 concavity (worst): 0.0 1.252 concave points...search in the space of 1-4 features and 1-3 separating planes....scikit-learn.org/stable/auto_examples/feature_selection/plot_select_from_model_diabetes.html -
Single estimator versus bagging: bias-variance ...
n_estimators - 1 : plt . legend ( loc = ( 1.1 , 0.5 )) plt ....axis = 1 )) ** 2 y_var = np . var ( y_predict , axis = 1 ) print...scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html -
label_ranking_average_precision_score — scikit-...
1 ], [ 1 , 0.2 , 0.1 ]]) >>> label_ranki...y_true = np . array ([[ 1 , 0 , 0 ], [ 0 , 0 , 1 ]]) >>> y_score =...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_average_precision_score.html -
Plot different SVM classifiers in the iris data...
plot the support vectors C = 1.0 # SVM regularization parameter...) X0 , X1 = X [:, 0 ], X [:, 1 ] for clf , title , ax in zip...scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html