Support Vector Machines
Support Vector Machines (SVM) is a supervised machine learning algorithm used for classification and regression analysis. SVM works by finding the hyperplane that maximizes the margin between the two classes. The hyperplane is the decision boundary that separates the data into different classes. SVM can handle both linear and non-linear data by using different kernel functions. SVM is effective in high-dimensional spaces and can handle large datasets. SVM is also used for outlier detection and clustering analysis.
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