Which of the following statements is true about Support Vector Machines? 1. SVMs are another technique for supervised classification. 2. SVMs are used for predicting a fractional, continuous variable always. 3. SVMs must always be kernelized! 4. SVMs work only if there are less than 20 components to a feature vector.
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SVMs are a type of supervised machine learning algorithm that can be used for both classification and regression tasks but are more commonly used in classification problems. Show more…
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