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t-SNE: The effect of various perplexity values ...
2 sec S-curve, perplexity=50 in...n_samples = 150 n_components = 2 ( fig , subplots ) = plt . subplots...scikit-learn.org/stable/auto_examples/manifold/plot_t_sne_perplexity.html -
Illustration of Gaussian process classification...
2 ) Y = np . logical_xor ( X [:,...DotProduct ( sigma_0 = 1.0 ) ** 2 ] for i , kernel in enumerate...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
Compare cross decomposition methods — sci...
[: n // 2 ] Y_train = Y [: n // 2 ] X_test = X [ n // 2 :] Y_test...that: Y = XB + Err) [[1 1 1] [2 2 2] [0 0 0] [0 0 0] [0 0 0] [0...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_compare_cross_decomposition.html -
Gaussian processes on discrete data structures ...
2.0 , 2.0 , 3.0 , 3.0 ]) training_idx...Y [ training_idx ], width = 0.2 , color = "r" , alpha...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Comparing Random Forests and Histogram Gradient...
col = 2 ) fig . add_trace ( line_trace , row = 1 , col = 2 ) fig..." ) Number of physical cores: 2 Unlike RF, HGBT models offer an...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_hist_grad_boosting_comparison.html -
Curve Fitting with Bayesian Ridge Regression &#...
sin ( 2 * np . pi * x ) size = 25 rng..., axes = plt . subplots ( 1 , 2 , figsize = ( 8 , 4 )) for i ,...scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html -
Effect of varying threshold for self-training &...
capsize = 2 , color = "b" ) ax1.... std ( axis = 1 ), capsize = 2 , color = "g" , ) ax2...scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html -
Detection error tradeoff (DET) curve — sc...
n_features = 2 , n_redundant = 0 , n_informative = 2 , random_state...ax_det ] = plt . subplots ( 1 , 2 , figsize = ( 11 , 5 )) ax_roc...scikit-learn.org/stable/auto_examples/model_selection/plot_det.html -
13. Choosing the right estimator — scikit...
Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data and different problem...scikit-learn.org/stable/machine_learning_map.html -
Categorical Feature Support in Gradient Boostin...
2, etc., and treated as continuous...ax2 ) = plt . subplots ( 1 , 2 , figsize = ( 12 , 8 )) plot_info...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html