Search Options

Display Count
Sort
Preferred Language
Label
Advanced Search

Results 1141 - 1150 of over 10,000 for 1 (0.2 seconds)

  1. Feature discretization — scikit-learn 1.7...

    logspace ( - 1 , 1 , 3 )}, ), ( make_pipeline (..."linearsvc__C" : np . logspace ( - 1 , 1 , 3 )}, ), ( make_pipeline (...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_classification.html
    Mon Nov 24 08:52:56 GMT 2025
      128.7K bytes
      Cache
     
  2. Classifier comparison — scikit-learn 1.7....

    C = 1 , random_state = 42 ), GaussianProcessClass ( 1.0 * RBF...max_features = 1 , random_state = 42 ), MLPClassifier ( alpha = 1 , max_iter...
    scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html
    Mon Nov 24 07:36:04 GMT 2025
      114.3K bytes
      Cache
     
  3. GMM covariances — scikit-learn 1.7.2 docu...

    shape [ 1 ]) * gmm . covariances_ [ n ]...]) angle = np . arctan2 ( u [ 1 ], u [ 0 ]) angle = 180 * angle...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html
    Mon Nov 24 08:52:54 GMT 2025
      108.4K bytes
      Cache
     
  4. Incremental PCA — scikit-learn 1.7.2 docu...

    scatterpoints = 1 ) plt . axis ([ - 4 , 4 , - 1.5 , 1.5 ]) plt . show...target_name in zip ( colors , [ 0 , 1 , 2 ], iris . target_names ):...
    scikit-learn.org/stable/auto_examples/decomposition/plot_incremental_pca.html
    Mon Nov 24 08:52:56 GMT 2025
      91.5K bytes
      Cache
     
  5. Logistic function — scikit-learn 1.7.2 do...

    1 ]) plt . ylim ( - 0.25 , 1.25 ) plt . xlim...classify values as either 0 or 1, i.e. class one or two, using...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic.html
    Mon Nov 24 08:52:54 GMT 2025
      95K bytes
      Cache
     
  6. 2.6. Covariance estimation — scikit-learn...

    1. Empirical covariance # The covariance...2.6.2. Shrunk Covariance # 2.6.2.1. Basic shrinkage # Despite being...
    scikit-learn.org/stable/modules/covariance.html
    Mon Nov 24 10:40:48 GMT 2025
      59.7K bytes
      Cache
     
  7. Isotonic Regression — scikit-learn 1.7.2 ...

    An illustration of the isotonic regression on generated data (non-linear monotonic trend with homoscedastic uniform noise). The isotonic regression algorithm finds a non-decreasing approximation of...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_isotonic_regression.html
    Mon Nov 24 08:52:53 GMT 2025
      114.1K bytes
      Cache
     
  8. sklearn.cluster — scikit-learn 1.7.2 docu...

    Popular unsupervised clustering algorithms. User guide. See the Clustering and Biclustering sections for further details.
    scikit-learn.org/stable/api/sklearn.cluster.html
    Mon Nov 24 08:52:53 GMT 2025
      123.1K bytes
      Cache
     
  9. sklearn.decomposition — scikit-learn 1.7....

    Matrix decomposition algorithms. These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be regarded as dimensionality reduction techniques. User guide. See the Decomposing...
    scikit-learn.org/stable/api/sklearn.decomposition.html
    Mon Nov 24 08:52:53 GMT 2025
      121.4K bytes
      Cache
     
  10. Model Selection — scikit-learn 1.7.2 docu...

    Examples related to the sklearn.model_selection module. Balance model complexity and cross-validated score Class Likelihood Ratios to measure classification performance Comparing randomized search ...
    scikit-learn.org/stable/auto_examples/model_selection/index.html
    Mon Nov 24 07:36:03 GMT 2025
      89K bytes
      Cache
     
Back to Top