Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 821 - 830 of 1,745 for document (2.33 sec)

  1. Robust covariance estimation and Mahalanobis di...

    This example shows covariance estimation with Mahalanobis distances on Gaussian distributed data. For Gaussian distributed data, the distance of an observation x_i to the mode of the distribution c...
    scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html
    Sat Oct 11 07:51:26 UTC 2025
      117.3K bytes
      Cache
     
  2. HuberRegressor vs Ridge on dataset with strong ...

    Fit Ridge and HuberRegressor on a dataset with outliers. The example shows that the predictions in ridge are strongly influenced by the outliers present in the dataset. The Huber regressor is less ...
    scikit-learn.org/stable/auto_examples/linear_model/plot_huber_vs_ridge.html
    Sat Oct 11 07:51:26 UTC 2025
      95.1K bytes
      Cache
     
  3. Robust linear model estimation using RANSAC — s...

    In this example, we see how to robustly fit a linear model to faulty data using the RANSAC algorithm. The ordinary linear regressor is sensitive to outliers, and the fitted line can easily be skewe...
    scikit-learn.org/stable/auto_examples/linear_model/plot_ransac.html
    Sat Oct 11 07:51:25 UTC 2025
      93.4K bytes
      Cache
     
  4. Class Likelihood Ratios to measure classificati...

    This example demonstrates the class_likelihood_ratios function, which computes the positive and negative likelihood ratios ( LR+, LR-) to assess the predictive power of a binary classifier. As we w...
    scikit-learn.org/stable/auto_examples/model_selection/plot_likelihood_ratios.html
    Sat Oct 11 07:51:26 UTC 2025
      143.3K bytes
      Cache
     
  5. Compare the effect of different scalers on data...

    Feature 0 (median income in a block) and feature 5 (average house occupancy) of the California Housing dataset have very different scales and contain some very large outliers. These two characteris...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html
    Sat Oct 11 07:51:25 UTC 2025
      138.2K bytes
      Cache
     
  6. Overview of multiclass training meta-estimators...

    In this example, we discuss the problem of classification when the target variable is composed of more than two classes. This is called multiclass classification. In scikit-learn, all estimators su...
    scikit-learn.org/stable/auto_examples/multiclass/plot_multiclass_overview.html
    Sat Oct 11 07:51:25 UTC 2025
      114.3K bytes
      Cache
     
  7. Label Propagation digits: Active learning — sci...

    Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model with only 10 labeled points, then we select the top fiv...
    scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni...
    Sat Oct 11 07:51:26 UTC 2025
      109.1K bytes
      Cache
     
  8. 9.3. Parallelism, resource management, and conf...

    n_jobs is currently poorly documented. Please help us by improving...explained by this piece of documentation . 9.3.1.3. Parallel NumPy...
    scikit-learn.org/stable/computing/parallelism.html
    Sat Oct 11 07:51:26 UTC 2025
      61K bytes
      Cache
     
  9. 9. Computing with scikit-learn — scikit-learn 1...

    Strategies to scale computationally: bigger data- Scaling with instances using out-of-core learning., Computational Performance- Prediction Latency, Prediction Throughput, Tips and Tricks., Paralle...
    scikit-learn.org/stable/computing.html
    Sat Oct 11 07:51:25 UTC 2025
      31.4K bytes
      Cache
     
  10. Plot different SVM classifiers in the iris data...

    Comparison of different linear SVM classifiers on a 2D projection of the iris dataset. We only consider the first 2 features of this dataset: Sepal length, Sepal width. This example shows how to pl...
    scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html
    Sat Oct 11 07:51:27 UTC 2025
      92.7K bytes
      Cache
     
Back to top