- Sort Score
- Num 10 results
- Language All
- Labels All
Results 971 - 980 of over 10,000 for * (6.26 seconds)
Filter
-
Linear and Quadratic Discriminant Analysis with...
seed = 0 , ) covariance = np . array ([[ 0.0 , - 0.23 ], [ 0.83 ,...seed = 0 , ) cov_class_1 = np . array ([[ 0.0 , - 1.0 ], [ 2.5...scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html -
A demo of K-Means clustering on the handwritten...
k-means++ 0.033s 69545 0.598 0.645 0.621 0.469 0.617 0.158 random...random 0.038s 69735 0.681 0.723 0.701 0.574 0.698 0.173 PCA-based...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_digits.html -
Release Highlights for scikit-learn 1.3 — sciki...
([ 0 , 1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 , 0...tree . predict ( X ) array([0, 0, 1, 1]) New display ValidationCurveDispl...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html -
Comparison of the K-Means and MiniBatchKMeans c...
left = 0.02 , right = 0.98 , bottom = 0.05 , top = 0.9 ) colors...seed ( 0 ) batch_size = 45 centers = [[ 1 , 1 ], [ - 1 , - 1 ], [...scikit-learn.org/stable/auto_examples/cluster/plot_mini_batch_kmeans.html -
sphinx-design.min.css
lex:1 0 0%;-ms-flex:1 0 0%}.sd-row-cols-auto>*{flex:0 0 auto...:scale(1.01)}.sd-card-body{-ms-flex:1 1 auto;flex:1 1 auto;padding:1rem...scikit-learn.org/stable/_static/sphinx-design.min.css -
Model Complexity Influence — scikit-learn 1.8.0...
"changing_param_values" : [ 0.05 , 0.1 , 0.2 , 0.35 , 0.5 ], "complexity_label"...NuSVR(C=1000.0, gamma=3.0517578125e-05, nu=0.05) Complexity: 18...scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html -
Gaussian Mixture Model Sine Curve — scikit-lear...
bottom = 0.04 , top = 0.95 , hspace = 0.2 , wspace = 0.05 , left...( - 6.0 , 4.0 * np . pi - 6.0 ) plt . ylim ( - 5.0 , 5.0 ) plt...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_sin.html -
Gradient Boosting regularization — scikit-learn...
random_state = 1 ) # map labels from {-1, 1} to {0, 1} labels , y..."learning_rate" : 1.0 , "subsample" : 1.0 }), ( "learning_rate=0.2" , "turquoise"...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regularization.html -
IsolationForest example — scikit-learn 1.8.0 do...
RandomState ( 0 ) covariance = np . array ([[ 0.5 , - 0.1 ], [ 0.7 , 0.4...be in the range (0, 0.5]. .. versionchanged:: 0.22 The default...scikit-learn.org/stable/auto_examples/ensemble/plot_isolation_forest.html -
Plot individual and voting regression predictio...
must be in the range `(0.0, 1.0]`. 1.0 criterion criterion: {'friedman_mse',...range `(0.0, 1.0)`. 0.9 verbose verbose: int, default=0 Enable...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_regressor.html