Support Vector Machines (SVM) are family of robust classification and regression techniques that maximize the predictive accuracy of a model without overfitting the training data. SVMs are particularly suited to analyzing data with very large numbers (for example, thousands) of predictor fields.
- For more information about this node, see Linear SVM Overview.
- For more information about the visualizations for this node, see Linear SVM Visualizations.
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