Intel(R) Extension for Scikit-learn*
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Get Started

  • Quick Start
    • Compatibility with Scikit-learn*
    • Integrate Intel® Extension for Scikit-learn*
      • Patching
      • Global Patching
      • Unpatching
    • Installation
      • Install from PyPI
      • Install from Anaconda* Cloud
      • Build from Sources
      • Install Intel*(R) AI Tools
    • Release Notes
    • System Requirements
      • Hardware Requirements
      • Software Requirements
      • Memory Requirements
  • Samples
    • k-Nearest Neighbors (kNN) for MNIST dataset
      • Download the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Logistic Regression for Cifar dataset
      • Download the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Support Vector Classification (SVC) for Adult dataset
      • Download the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • ElasticNet for Airlines DepDelay dataset
      • Download the data
      • Preprocessing
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Lasso Regression for YearPredictionMSD dataset
      • Download the data
      • Normalize the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Linear Regression for YearPredictionMSD dataset
      • Download the data
      • Normalize the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Nu-Support Vector Regression (NuSVR) for Medical Charges dataset
      • Download the data
      • Preprocessing
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Random Forest for Yolanda dataset
      • Download the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Rigde Regression for Airlines DepDelay dataset
      • Download the data
      • Preprocessing
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Kmeans for spoken arabic digit dataset
      • Download the data
      • Preprocessing
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • DBSCAN for spoken arabic digit dataset
      • Download the data
      • Preprocessing
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Train the same algorithm with original Scikit-learn
    • Intel® Extension for Scikit-learn TSNE example
      • Generate the data
      • Patch original Scikit-learn with Intel® Extension for Scikit-learn
      • Plot embeddings original scikit-learn and Intel® extension
    • Intel® Extension for Scikit-Learn* Getting Started Sample
    • Intel® Extension for Scikit-Learn*: SVC for Adult dataset Performance Sample
  • Kaggle Kernels
    • Acceleration
    • Machine Learning Workflows
      • Kaggle kernels that use scikit-learn and Intel® Extension for Scikit-learn*:
        • Classification Tasks
          • Binary Classification
          • MultiClass Classification
          • Classification Tasks in Computer Vision
          • Classification Tasks in Natural Language Processing
        • Regression Tasks
          • Using a Single Regressor
          • Stacking Regressors
      • Kaggle kernels that use AutoML with Intel® Extension for Scikit-learn*:
        • AutoML Workflows

Developer Guide

  • Supported Algorithms
    • on CPU
      • Classification
      • Regression
      • Clustering
      • Dimensionality Reduction
      • Nearest Neighbors
      • Other Tasks
    • on GPU
      • Classification
      • Regression
      • Clustering
      • Dimensionality Reduction
      • Nearest Neighbors
      • Other Tasks
    • SPMD Support
      • Classification
      • Regression
      • Clustering
      • Dimensionality Reduction
      • Nearest Neighbors
      • Other Tasks
    • Scikit-learn Tests
  • oneAPI and GPU support
    • Prerequisites
    • Device offloading
    • Example
  • Distributed Mode
  • Non-Scikit-Learn Algorithms
    • BasicStatistics
      • BasicStatistics
        • BasicStatistics.min_
        • BasicStatistics.max_
        • BasicStatistics.sum_
        • BasicStatistics.mean_
        • BasicStatistics.variance_
        • BasicStatistics.variation_
        • BasicStatistics.sum_squares_
        • BasicStatistics.standard_deviation_
        • BasicStatistics.sum_squares_centered_
        • BasicStatistics.second_order_raw_moment_
      • BasicStatistics.fit()
    • IncrementalBasicStatistics
      • IncrementalBasicStatistics
        • IncrementalBasicStatistics.min_
        • IncrementalBasicStatistics.max_
        • IncrementalBasicStatistics.sum_
        • IncrementalBasicStatistics.mean_
        • IncrementalBasicStatistics.variance_
        • IncrementalBasicStatistics.variation_
        • IncrementalBasicStatistics.sum_squares_
        • IncrementalBasicStatistics.standard_deviation_
        • IncrementalBasicStatistics.sum_squares_centered_
        • IncrementalBasicStatistics.second_order_raw_moment_
        • IncrementalBasicStatistics.n_samples_seen_
        • IncrementalBasicStatistics.batch_size_
        • IncrementalBasicStatistics.n_features_in_
      • IncrementalBasicStatistics.fit()
      • IncrementalBasicStatistics.partial_fit()
    • IncrementalEmpiricalCovariance
      • IncrementalEmpiricalCovariance
        • IncrementalEmpiricalCovariance.location_
        • IncrementalEmpiricalCovariance.covariance_
        • IncrementalEmpiricalCovariance.n_samples_seen_
        • IncrementalEmpiricalCovariance.batch_size_
        • IncrementalEmpiricalCovariance.n_features_in_
      • IncrementalEmpiricalCovariance.fit()
      • IncrementalEmpiricalCovariance.partial_fit()
    • IncrementalLinearRegression
      • IncrementalLinearRegression
        • IncrementalLinearRegression.coef_
        • IncrementalLinearRegression.intercept_
        • IncrementalLinearRegression.n_samples_seen_
        • IncrementalLinearRegression.batch_size_
        • IncrementalLinearRegression.n_features_in_
      • IncrementalLinearRegression.fit()
      • IncrementalLinearRegression.partial_fit()
      • IncrementalLinearRegression.predict()
  • Supported input types
  • Array API support
    • Support for DPNP and DPCTL
    • Support for Array API-compatible inputs
    • Example usage
      • DPNP ndarrays
      • DPCTL usm_ndarrays
      • Use of array-api-strict
  • Verbose Mode
  • Preview Functionality
  • Deprecation Notice
    • macOS* Support

Performance

  • Tuning Guide
    • TSNE
    • Random Forest

Learn

  • Tutorials & Case Studies
    • Tutorials
    • Case Studies
  • Medium Blogs

More

  • Support
    • Issues
  • How to Contribute
    • Licensing
    • Pull Requests
      • Before Contributing Changes
    • Code Style
  • License
Intel(R) Extension for Scikit-learn*
  • License
  • View page source

License

License: https://github.com/intel/scikit-learn-intelex/blob/main/LICENSE

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