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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When the C parameter is set to infinite, which of the following holds true?
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The optimal hyperplane if exists, will be the one that completely separates the data
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The soft-margin classifier will separate the data
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None of the above
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None of the above
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Explanation:
Detailed explanation-1: -C is a regularization parameter that controls the trade off between the achieving a low training error and a low testing error that is the ability to generalize your classifier to unseen data.
Detailed explanation-2: -But what happens when there is no clear hyperplane? This is where it can get tricky. Data is rarely ever as clean as our simple example above. A dataset will often look more like the jumbled balls below which represent a linearly non separable dataset.
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