Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 741 - 750 of 3,151 for 2 (0.98 sec)

  1. Gaussian Mixture Models — scikit-learn 1.7.2 do...

    Examples concerning the sklearn.mixture module. Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture Density Estimation for a Gaussian mixture GMM Initialization Methods GMM cov...
    scikit-learn.org/stable/auto_examples/mixture/index.html
    Tue Sep 23 15:14:21 UTC 2025
      77.3K bytes
      Cache
     
  2. sklearn.calibration — scikit-learn 1.7.2 docume...

    Methods for calibrating predicted probabilities. User guide. See the Probability calibration section for further details. Visualization:
    scikit-learn.org/stable/api/sklearn.calibration.html
    Tue Sep 23 15:14:23 UTC 2025
      115.4K bytes
      Cache
     
  3. fetch_20newsgroups — scikit-learn 1.7.2 documen...

    Gallery examples: Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation Biclustering documents with the Spectral Co-clustering algorithm Column Transformer with He...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups.html
    Tue Sep 23 15:14:21 UTC 2025
      119.5K bytes
      Cache
     
  4. sklearn.cluster — scikit-learn 1.7.2 documentation

    Popular unsupervised clustering algorithms. User guide. See the Clustering and Biclustering sections for further details.
    scikit-learn.org/stable/api/sklearn.cluster.html
    Tue Sep 23 15:14:21 UTC 2025
      123.1K bytes
      Cache
     
  5. shrunk_covariance — scikit-learn 1.7.2 document...

    Skip to main content Back to top Ctrl + K GitHub Choose version shrunk_covariance # sklearn.covariance. shrunk_covari...
    scikit-learn.org/stable/modules/generated/sklearn.covariance.shrunk_covariance.html
    Tue Sep 23 15:14:23 UTC 2025
      108.5K bytes
      Cache
     
  6. sklearn.decomposition — scikit-learn 1.7.2 docu...

    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
    Tue Sep 23 15:14:23 UTC 2025
      121.4K bytes
      Cache
     
  7. top_k_accuracy_score — scikit-learn 1.7.2 docum...

    2 , 2 ]) >>> y_score = np . array ([[ 0.5 , 0.2 , 0.2 ], #...top 2 ... [ 0.3 , 0.4 , 0.2 ], # 1 is in top 2 ... [ 0.2 , 0.4...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html
    Tue Sep 23 15:14:23 UTC 2025
      112.5K bytes
      1 views
      Cache
     
  8. Plot the decision surfaces of ensembles of tree...

    2 , w_pad = 0.2 , pad = 2.5 ) plt . show ()...pair in ([ 0 , 1 ], [ 0 , 2 ], [ 2 , 3 ]): for model in models...
    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_iris.html
    Tue Sep 23 15:14:21 UTC 2025
      113.9K bytes
      Cache
     
  9. SGD: Maximum margin separating hyperplane — sci...

    centers = 2 , random_state = 0 , cluster_std...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html
    Tue Sep 23 15:14:23 UTC 2025
      90.8K bytes
      Cache
     
  10. Various Agglomerative Clustering on a 2D embedd...

    SpectralEmbedding ( n_components = 2 ) . fit_transform ( X ) print...
    scikit-learn.org/stable/auto_examples/cluster/plot_digits_linkage.html
    Tue Sep 23 15:14:21 UTC 2025
      95.2K bytes
      Cache
     
Back to top