scikit-learn-extra
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1. EigenPro for Regression and Classification
2. Clustering with KMedoids, CLARA and Common-nearest-neighbors
3. Robust algorithms for Regression, Classification and Clustering
4. Kernel map approximation for faster kernel methods
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scikit-learn-extra
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User guide
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1. EigenPro for Regression and Classification
2. Clustering with KMedoids, CLARA and Common-nearest-neighbors
2.1. K-Medoids
2.2. CLARA
2.3. Common-nearest-neighbors clustering
3. Robust algorithms for Regression, Classification and Clustering
3.1. What is an outlier ?
3.2. Robust estimation with robust weighting
3.3. Robust estimation in practice
3.3.1. The algorithm
3.3.2. Comparison with other robust estimators
3.3.3. Speed and limits of the algorithm
4. Kernel map approximation for faster kernel methods
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