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8.3. Parallelism, resource management, and conf...
1.1. Higher-level parallelism with...management, and configuration # 8.3.1. Parallelism # Some scikit-learn...scikit-learn.org/dev/computing/parallelism.html -
Plot classification boundaries with different S...
1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 ]) # Plotting settings...], [ - 1.5 , - 1.0 ], [ - 1.4 , - 0.9 ], [ - 1.3 , - 1.2 ], [...scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html -
Normal, Ledoit-Wolf and OAS Linear Discriminant...
n_features_range = range ( 1 , n_features_max + 1 , step ) for n_features...n_samples = n_samples , n_features = 1 , centers = [[ - 2 ], [ 2 ]])...scikit-learn.org/stable/auto_examples/classification/plot_lda.html -
Feature importances with a forest of trees — sc...
shape [ 1 ])] forest = RandomForestClassifi...time of the script: (0 minutes 1.193 seconds) Download Jupyter...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html -
Statistical comparison of models using grid sea...
\[t=\frac{\frac{1}{k \cdot r}\sum_{i=1}^{k}\sum_{j=1}^{r}x_{ij}}...p-values higher than 1 p_val = 1 if p_val > 1 else p_val pairwise_t_test...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_stats.html -
Concatenating multiple feature extraction metho...
features__univ_select__k=1, svm__C=0.1 [CV 1/5; 1/18] END features_...nts=1, features__univ_select__k=1, svm__C=0.1;, score=1.000 total...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
Part 10: How to build in Windows environment
1. Click “New” of “System environment variable”. 1. Enter...version). 1. In System Variables, select Path and click Edit. 1. In...fess.codelibs.org/articles/10/document.html -
Comparison of F-test and mutual information — s...
follows: y = x_1 + sin(6 * pi * x_2) + 0.1 * N(0, 1), that is the...features x_1, x_2, x_3 distributed uniformly over [0, 1], the target...scikit-learn.org/stable/auto_examples/feature_selection/plot_f_test_vs_mi.html -
Post-hoc tuning the cut-off point of decision f...
boxplot ( ax = ax [ 1 ]) ax [ 1 ] . set_title ( "Tuned model"...scikit-learn 1.5 Release Highlights for scikit-learn 1.5 Effect of...scikit-learn.org/stable/auto_examples/model_selection/plot_tuned_decision_threshold.html -
Plot class probabilities calculated by the Voti...
[ 1.1 , 1.2 ]]) y = np . array ([ 1 , 1 , 2 , 2 ]) eclf...np . array ([[ - 1.0 , - 1.0 ], [ - 1.2 , - 1.4 ], [ - 3.4 , -...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_probas.html