APPLICATION OF SUPERVISED LEARNING
SUPPORT VECTOR MACHINE SVM
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Misclassification would happen
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Data will be correctly classified
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Can’t say
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None of these
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Detailed explanation-1: -Q13. What would happen when you use a very small C (C 0)? Explanation: The classifier can maximize the margin between most of the points while misclassifying a few points because the penalty is so low.
Detailed explanation-2: -– If the values of C are very small the margin increases thus Soft SVM. – Large value of C can cause overfitting therefore we need to select the correct value using Hyperparameter Tuning.
Detailed explanation-3: -Higher values of C lead to Overfitting resulting in a low bias and high variance.
Detailed explanation-4: -C adds penalty to each misclassified point. If the C value is small, then essentially, the penalty for misclassified points is also small, thus resulting in a larger margin based boundary. If the C value is large, then SVM tries to minimize the number of misclassified points by reducing the margin width.