support vector machines
Support Vector Machines (SVM) is a supervised machine learning algorithm that is used for classification and regression analysis. SVMs are essentially a set of lines or curves called hyperplanes, which are used to classify data points. The algorithm works by identifying the hyperplane that best separates the data into different classes, while also maximizing the distance (margin) between the hyperplane and the data points. SVMs are particularly useful in situations where the data is not linearly separable, as they can also use non-linear decision boundaries to classify the data. Overall, SVMs are a powerful and versatile machine learning technique that has been widely adopted for a range of different applications.
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