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Bookmark or Share- Support vector machine - WikipediaIn machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised max-margin models with associated learning algorithms that analyze data for classification and regression analysis.
- Support Vector Machines (SVM): An Intuitive ExplanationSupport Vector Machines (SVMs) are a type of supervised machine learning algorithm used for classification and regression tasks. They are widely used in various fields,...
- Guide on Support Vector Machine (SVM) Algorithm - Analytics VidhyaA popular and reliable supervised machine learning technique called Support Vector Machine (SVM) was first created for classification tasks, though it can also be modified to solve regression issues. The goal of SVM is to locate in the feature space the optimal separation hyperplane between classes.
- Support Vector Machine (SVM) Algorithm - GeeksforGeeksA Support Vector Machine (SVM) is a powerful machine learning algorithm widely used for both linear and nonlinear classification, as well as regression and outlier detection tasks. SVMs are highly adaptable, making them suitable for various applications such as text classification, image classification, spam detection, handwriting ...
- 1.4. Support Vector Machines — scikit-learn 1.5.2 documentationSupport vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. The advantages of support vector machines are: Effective in high ...
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