HTML documentation (development version):https://scikit-learn.org/dev/ FAQ:https://scikit-learn.org/stable/faq.html Communication Mailing list:https://mail.python.org/mailman/listinfo/scikit-learn Logos & Branding:https://github.com/scikit-learn/scikit-learn/tree/main/doc/logos ...
sklearn.neighbors.KNeighborsClassifier — scikit-learn 0.20.2 documentation https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html#sklearn.neighbors.KNeighborsClassifier class sklearn.neighbors.KNeighborsClassifier(n_neighbors=5, weights=’uniform’, algorithm=’auto...
Documentation:http://contrib.scikit-learn.org/category_encoders/ Encoding Methods Unsupervised: Backward Difference Contrast [2][3] BaseN [6] Binary [5] Gray [14] Count [10] Hashing [1] Helmert Contrast [2][3] Ordinal [2][3] One-Hot [2][3] ...
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The Scikit-learn documentation is good, and theexamplesare many — about 200 in total. Most examples include at least one graph produced from the analyzed data using Matplotlib. These all contribute to the library’s ease of development and its ease of learning. ...
Useful Resources Intel AI Developer Tools and resources oneAPI unified programming model and oneDAL library Intel® Extension for Scikit-learn* - documentation
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Scikit-learn is a powerful machine learning library that’s a great place for beginners to get their feet wet. Here’s a guide to getting started with it.
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Intel® Extension for Scikit-learnprovides drop-in replacement patching functionality for a seamless way to speed up your Scikit-learn application. We achieve this through the use of theIntel® oneAPI Data Analytics Library(oneDAL) and its convenientPython API daal4pypowering the extension underne...