Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of its hyper parameter.What would happen when you use very small C (C~0)?

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data will be correctly classified

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misclassification would happen

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cant say

TuteeHUB · Answer

none of these

1.	Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of its hyper parameter.What would happen when you use very small C (C~0)?
A.	misclassification would happen
B.	data will be correctly classified
C.	cant say
D.	none of these
Answer» B. data will be correctly classified

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