Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 301 - 310 of 1,745 for document (1.37 sec)

  1. make_friedman2 — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version make_friedman2 # sklearn.datasets. make_friedman2 ( n...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html
    Thu Oct 09 16:57:48 UTC 2025
      110.5K bytes
      Cache
     
  2. check_increasing — scikit-learn 1.7.2 documenta...

    Skip to main content Back to top Ctrl + K GitHub Choose version check_increasing # sklearn.isotonic. check_increasing...
    scikit-learn.org/stable/modules/generated/sklearn.isotonic.check_increasing.html
    Thu Oct 09 16:57:49 UTC 2025
      107.2K bytes
      Cache
     
  3. sklearn.impute — scikit-learn 1.7.2 documentation

    Transformers for missing value imputation. User guide. See the Imputation of missing values section for further details.
    scikit-learn.org/stable/api/sklearn.impute.html
    Thu Oct 09 16:57:47 UTC 2025
      115.3K bytes
      Cache
     
  4. f_regression — scikit-learn 1.7.2 documentation

    Gallery examples: Feature agglomeration vs. univariate selection Comparison of F-test and mutual information
    scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_regression.html
    Thu Oct 09 16:57:49 UTC 2025
      118.1K bytes
      Cache
     
  5. Vector Quantization Example — scikit-learn 1.7....

    This example shows how one can use KBinsDiscretizer to perform vector quantization on a set of toy image, the raccoon face. Original image: We start by loading the raccoon face image from SciPy. We...
    scikit-learn.org/stable/auto_examples/cluster/plot_face_compress.html
    Thu Oct 09 16:57:48 UTC 2025
      111.1K bytes
      Cache
     
  6. sklearn.compose — scikit-learn 1.7.2 documentation

    Meta-estimators for building composite models with transformers. In addition to its current contents, this module will eventually be home to refurbished versions of Pipeline and FeatureUnion. User ...
    scikit-learn.org/stable/api/sklearn.compose.html
    Thu Oct 09 16:57:45 UTC 2025
      116.5K bytes
      Cache
     
  7. make_blobs — scikit-learn 1.7.2 documentation

    Gallery examples: Probability calibration of classifiers Probability Calibration for 3-class classification Normal, Ledoit-Wolf and OAS Linear Discriminant Analysis for classification Demo of affin...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_blobs.html
    Thu Oct 09 16:57:48 UTC 2025
      130.3K bytes
      Cache
     
  8. fetch_rcv1 — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version fetch_rcv1 # sklearn.datasets. fetch_rcv1 ( * , data_...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_rcv1.html
    Thu Oct 09 16:57:49 UTC 2025
      112K bytes
      Cache
     
  9. empirical_covariance — scikit-learn 1.7.2 docum...

    Gallery examples: Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood
    scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html
    Thu Oct 09 16:57:45 UTC 2025
      108.7K bytes
      Cache
     
  10. cosine_distances — scikit-learn 1.7.2 documenta...

    Skip to main content Back to top Ctrl + K GitHub Choose version cosine_distances # sklearn.metrics.pairwise. cosine_d...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_distances.html
    Thu Oct 09 16:57:45 UTC 2025
      107.7K bytes
      Cache
     
Back to top