Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 611 - 620 of 1,679 for document (0.63 sec)

  1. Curve Fitting with Bayesian Ridge Regression — ...

    Computes a Bayesian Ridge Regression of Sinusoids. See Bayesian Ridge Regression for more information on the regressor. In general, when fitting a curve with a polynomial by Bayesian ridge regressi...
    scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html
    Sat Apr 19 00:31:22 UTC 2025
      98.2K bytes
      Cache
     
  2. Categorical Feature Support in Gradient Boostin...

    In this example, we will compare the training times and prediction performances of HistGradientBoostingRegressor with different encoding strategies for categorical features. In particular, we will ...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html
    Sat Apr 19 00:31:21 UTC 2025
      125.1K bytes
      Cache
     
  3. Plotting Cross-Validated Predictions — scikit-l...

    This example shows how to use cross_val_predict together with PredictionErrorDisplay to visualize prediction errors. We will load the diabetes dataset and create an instance of a linear regression ...
    scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html
    Sat Apr 19 00:31:22 UTC 2025
      92.2K bytes
      Cache
     
  4. zero_one_loss — scikit-learn 1.6.1 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version zero_one_loss # sklearn.metrics. zero_one_loss ( y_tr...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.html
    Sat Apr 19 00:31:22 UTC 2025
      110.7K bytes
      Cache
     
  5. Ridge coefficients as a function of the L2 Regu...

    A model that overfits learns the training data too well, capturing both the underlying patterns and the noise in the data. However, when applied to unseen data, the learned associations may not hol...
    scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_coeffs.html
    Sat Apr 19 00:31:21 UTC 2025
      103.2K bytes
      Cache
     
  6. estimator_html_repr — scikit-learn 1.6.1 docume...

    Skip to main content Back to top Ctrl + K GitHub Choose version estimator_html_repr # sklearn.utils. estimator_html_r...
    scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_html_repr.html
    Sat Apr 19 00:31:22 UTC 2025
      105.9K bytes
      Cache
     
  7. dict_learning_online — scikit-learn 1.6.1 docum...

    Skip to main content Back to top Ctrl + K GitHub Choose version dict_learning_online # sklearn.decomposition. dict_le...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.dict_learning_online.html
    Sat Apr 19 00:31:22 UTC 2025
      123.5K bytes
      Cache
     
  8. sklearn.kernel_ridge — scikit-learn 1.6.1 docum...

    Kernel ridge regression. User guide. See the Kernel ridge regression section for further details.
    scikit-learn.org/stable/api/sklearn.kernel_ridge.html
    Sat Apr 19 00:31:22 UTC 2025
      114.7K bytes
      Cache
     
  9. 7. Dataset loading utilities — scikit-learn 1.6...

    The sklearn.datasets package embeds some small toy datasets and provides helpers to fetch larger datasets commonly used by the machine learning community to benchmark algorithms on data that comes ...
    scikit-learn.org/stable/datasets.html
    Sat Apr 19 00:31:21 UTC 2025
      38.4K bytes
      Cache
     
  10. Gaussian processes on discrete data structures ...

    This example illustrates the use of Gaussian processes for regression and classification tasks on data that are not in fixed-length feature vector form. This is achieved through the use of kernel f...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html
    Sat Apr 19 00:31:21 UTC 2025
      120.7K bytes
      1 views
      Cache
     
Back to top