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What is Support Vector Machines Overview about?

Support Vector Machines (SVMs) are supervised learning methods used for classification, regression, and outlier detection, known for their effectiveness in high-dimensional spaces and memory efficiency. They have advantages such as versatility with kernel functions but can face challenges like overfitting and lack of direct probability estimates. The scikit-learn library provides various SVM implementations for classification (SVC, NuSVC, LinearSVC) and regression (SVR, NuSVR, LinearSVR), along with feature

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etalieezechiel

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