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fetch_species_distributions — scikit-learn 1.5....
Gallery examples: Species distribution modeling Kernel Density Estimate of Species Distributionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.html -
load_sample_image — scikit-learn 1.5.2 document...
Gallery examples: Color Quantization using K-Meansscikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_image.html -
Plot individual and voting regression predictio...
A voting regressor is an ensemble meta-estimator that fits several base regressors, each on the whole dataset. Then it averages the individual predictions to form a final prediction. We will use th...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_regressor.html -
Examples based on real world datasets — scikit-...
Applications to real world problems with some medium sized datasets or interactive user interface. Compressive sensing: tomography reconstruction with L1 prior (Lasso) Faces recognition example usi...scikit-learn.org/stable/auto_examples/applications/index.html -
fetch_20newsgroups_vectorized — scikit-learn 1....
Gallery examples: Model Complexity Influence Multiclass sparse logistic regression on 20newgroups The Johnson-Lindenstrauss bound for embedding with random projectionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups_vectorized.html -
sklearn.naive_bayes — scikit-learn 1.5.2 docume...
Naive Bayes algorithms. These are supervised learning methods based on applying Bayes’ theorem with strong (naive) feature independence assumptions. User guide. See the Naive Bayes section for furt...scikit-learn.org/stable/api/sklearn.naive_bayes.html -
sklearn.kernel_approximation — scikit-learn 1.5...
Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.scikit-learn.org/stable/api/sklearn.kernel_approximation.html -
register_parallel_backend — scikit-learn 1.5.2 ...
Skip to main content Back to top Ctrl + K GitHub register_parallel_backend # sklearn.utils. register_parallel_backend...scikit-learn.org/stable/modules/generated/sklearn.utils.register_parallel_backend.html -
Installing the development version of scikit-le...
2.0), threadpoolctl (>= 3.1.0)....tests requires: pytest >= 7.1.2 Some tests also require pandas...scikit-learn.org/stable/developers/advanced_installation.html -
Post-tuning the decision threshold for cost-sen...
# (2) in Elkan paper [2]_. gain_matrix = np...metric" , ) axs [ 2 ] . legend () axs [ 2 ] . set_xlabel ( "Decision...scikit-learn.org/stable/auto_examples/model_selection/plot_cost_sensitive_learning.html