Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 791 - 800 of 2,956 for 1 (0.1 sec)

  1. sklearn.discriminant_analysis — scikit-learn 1....

    Linear and quadratic discriminant analysis. User guide. See the Linear and Quadratic Discriminant Analysis section for further details.
    scikit-learn.org/stable/api/sklearn.discriminant_analysis.html
    Mon Apr 21 17:07:39 UTC 2025
      115.4K bytes
      Cache
     
  2. sklearn.linear_model — scikit-learn 1.6.1 docum...

    A variety of linear models. User guide. See the Linear Models section for further details. The following subsections are only rough guidelines: the same estimator can fall into multiple categories,...
    scikit-learn.org/stable/api/sklearn.linear_model.html
    Mon Apr 21 17:07:38 UTC 2025
      135.9K bytes
      Cache
     
  3. sklearn.semi_supervised — scikit-learn 1.6.1 do...

    Semi-supervised learning algorithms. These algorithms utilize small amounts of labeled data and large amounts of unlabeled data for classification tasks. User guide. See the Semi-supervised learnin...
    scikit-learn.org/stable/api/sklearn.semi_supervised.html
    Mon Apr 21 17:07:39 UTC 2025
      115.8K bytes
      Cache
     
  4. clear_data_home — scikit-learn 1.6.1 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version clear_data_home # sklearn.datasets. clear_data_home (...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.clear_data_home.html
    Mon Apr 21 17:07:40 UTC 2025
      105.5K bytes
      Cache
     
  5. make_spd_matrix — scikit-learn 1.6.1 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version make_spd_matrix # sklearn.datasets. make_spd_matrix (...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_spd_matrix.html
    Mon Apr 21 17:07:39 UTC 2025
      107.1K bytes
      Cache
     
  6. get_scorer_names — scikit-learn 1.6.1 documenta...

    Skip to main content Back to top Ctrl + K GitHub Choose version get_scorer_names # sklearn.metrics. get_scorer_names ...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer_names.html
    Mon Apr 21 17:07:39 UTC 2025
      106K bytes
      Cache
     
  7. Non-negative least squares — scikit-learn 1.6.1...

    In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...
    scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html
    Mon Apr 21 17:07:38 UTC 2025
      93.3K bytes
      Cache
     
  8. mean_shift — scikit-learn 1.6.1 documentation

    array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...6. ], [1.33..., 0.66...]]) >>> labels array([1, 1, 1, 0, 0, 0])...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.mean_shift.html
    Mon Apr 21 17:07:39 UTC 2025
      112.3K bytes
      Cache
     
  9. set_config — scikit-learn 1.6.1 documentation

    Added in version 1.1. enable_cython_pairwise_dist...configuration setting. Added in version 1.1. array_api_dispatch bool, default=None...
    scikit-learn.org/stable/modules/generated/sklearn.set_config.html
    Mon Apr 21 17:07:39 UTC 2025
      120.3K bytes
      Cache
     
  10. SVM Margins Example — scikit-learn 1.6.1 docume...

    0 ] * 20 + [ 1 ] * 20 # figure number fignum = 1 # fit the model...is sqrt(1+a^2) away vertically in # 2-d. margin = 1 / np . sqrt...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_margin.html
    Mon Apr 21 17:07:38 UTC 2025
      100K bytes
      Cache
     
Back to top