Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 541 - 550 of 2,485 for 2 (0.07 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
    Mon Nov 10 15:11:18 UTC 2025
      77.3K bytes
      Cache
     
  2. 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
    Mon Nov 10 15:11:18 UTC 2025
      121.4K 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
    Mon Nov 10 15:11:18 UTC 2025
      119.5K bytes
      Cache
     
  4. 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
    Mon Nov 10 15:11:19 UTC 2025
      108.5K bytes
      Cache
     
  5. 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
    Mon Nov 10 15:11:18 UTC 2025
      115.4K bytes
      Cache
     
  6. FeatureUnion — scikit-learn 1.7.2 documentation

    n_components = 2 ))]) >>> X = [[ 0. , 1. , 3 ], [ 2. , 2. , 5 ]] >>>...parameters. Added in version 1.2. n_features_in_ int Number of...
    scikit-learn.org/stable/modules/generated/sklearn.pipeline.FeatureUnion.html
    Mon Nov 10 15:11:19 UTC 2025
      134.5K bytes
      Cache
     
  7. OutputCodeClassifier — scikit-learn 1.7.2 docum...

    Artificial Intelligence Research 2, 1995. [ 2 ] “The error coding method...n_features = 4 , ... n_informative = 2 , n_redundant = 0 , ... random_state...
    scikit-learn.org/stable/modules/generated/sklearn.multiclass.OutputCodeClassifier.html
    Mon Nov 10 15:11:19 UTC 2025
      132.1K bytes
      Cache
     
  8. Faces recognition example using eigenfaces and ...

    for machine learning we use the 2 data directly (as relative pixel...figure ( figsize = ( 1.8 * n_col , 2.4 * n_row )) plt . subplots_adjust...
    scikit-learn.org/stable/auto_examples/applications/plot_face_recognition.html
    Mon Nov 10 15:11:18 UTC 2025
      113.1K bytes
      Cache
     
  9. Gaussian Process for Machine Learning — scikit-...

    Examples concerning the sklearn.gaussian_process module. Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecas...
    scikit-learn.org/stable/auto_examples/gaussian_process/index.html
    Mon Nov 10 15:11:15 UTC 2025
      80.1K bytes
      Cache
     
  10. PoissonRegressor — scikit-learn 1.7.2 documenta...

    determination R^2. R^2 uses squared error and D^2 uses the deviance...PoissonRegressor () >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.PoissonRegressor.html
    Mon Nov 10 15:11:18 UTC 2025
      139.5K bytes
      Cache
     
Back to top