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  1. scikit-learn: machine learning in Python — scikit-learn 1.7.2 …

    scikit-learn Machine Learning in Python Getting Started Release Highlights for 1.7

  2. Installing scikit-learn — scikit-learn 1.7.2 documentation

    Install the version of scikit-learn provided by your operating system or Python distribution. This is a quick option for those who have operating systems or Python distributions that distribute …

  3. Examples — scikit-learn 1.7.2 documentation

    This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the API in general and some demonstrate specific applications in …

  4. API Reference — scikit-learn 1.7.2 documentation

    This is the class and function reference of scikit-learn. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full …

  5. Getting Started — scikit-learn 1.7.2 documentation

    Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, …

  6. User Guide — scikit-learn 1.7.2 documentation

    Jan 1, 2010 · 9. Computing with scikit-learn 9.1. Strategies to scale computationally: bigger data 9.1.1. Scaling with instances using out-of-core learning 9.2. Computational Performance 9.2.1. …

  7. train_test_split — scikit-learn 1.7.2 documentation

    Gallery examples: Image denoising using kernel PCA Faces recognition example using eigenfaces and SVMs Model Complexity Influence Prediction Latency Lagged features for …

  8. KMeans — scikit-learn 1.7.2 documentation

    Empirical evaluation of the impact of k-means initialization Comparison of the K-Means and MiniBatchKMeans clustering algorithms Release Highlights for scikit-learn 0.23 Release …

  9. 1. Supervised learning — scikit-learn 1.7.2 documentation

    Jan 1, 2010 · Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, …

  10. 1.6. Nearest Neighbors — scikit-learn 1.7.2 documentation

    In scikit-learn, ball-tree-based neighbors searches are specified using the keyword algorithm = 'ball_tree', and are computed using the class BallTree. Alternatively, the user can work with …