Samples

The following samples are also provided as Jupyter notebooks in Intel® Extension for Scikit-learn* repository. If you want to run them locally, refer to these instructions.

Classification Tasks

• k-Nearest Neighbors (kNN) for MNIST dataset
• Logistic Regression for Cifar dataset
• Support Vector Classification (SVC) for Adult dataset

Regression Tasks

• ElasticNet for Airlines DepDelay dataset
• Lasso Regression for YearPredictionMSD dataset
• Linear Regression for YearPredictionMSD dataset
• Nu-Support Vector Regression (NuSVR) for Medical Charges dataset
• Random Forest for Yolanda dataset
• Rigde Regression for Airlines DepDelay dataset

Clustering Tasks

• Kmeans for spoken arabic digit dataset
• DBSCAN for spoken arabic digit dataset

Jupyter Notebook Samples

• Intel® Extension for Scikit-Learn* Getting Started Sample
• Intel® Extension for Scikit-Learn*: SVC for Adult dataset Performance Sample

See also

There are also Kaggle kernels that use Intel® Extension for Scikit-learn* for a variety of machine learning scenarios.

Note

Explore the complete list of oneAPI code samples in the oneAPI Samples Catalog. These samples were designed to help you develop, offload, and optimize multiarchitecture applications targeting CPUs, GPUs, and FPGAs.