Support Vector Machines
Support Vector Machines (SVM) are machine learning algorithms used to classify and analyze data. SVMs are powerful as they can solve complex equations to classify data points and make decisions about them. They detect non-linear features and perform classification effectively. Furthermore, they are less prone to over-fitting and can be used for regression and probability estimation. SVMs are widely used for text classification and image classification, as well as for predicting stock prices or other numerical values. Through their use of a margin to optimize accuracy, SVMs can provide a robust solution for many data-driven problems.
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