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Reviews & Ratings
В машинном обучении используется широкий спектр важных алгоритмов и методик. Список алгоритмов машинного обучения приведен ниже: Алгоритм машины опорных векторов, алгоритм классификации "дерево решений", алгоритм "случайный лес", алгоритм логистической регрессии, алгоритм линейной регрессии, алгоритм K-Nearest Neighbor (KNN), алгоритм классификатора Naïve Bayes, алгоритм кластеризации K-Means, алгоритм XG-Boost.
Эти алгоритмы используются в самых разных областях, таких как робототехника, маркетинг, здравоохранение и финансы, и составляют основу машинного обучения. Выбор алгоритма зависит от характера проблемы, характеристик данных и доступных вычислительных мощностей.
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