In reality, you may find that you either cannot find a linearly separable dimension for your dataset for machine learning, or you may find that your support vector machine has significant overfitment to your data. You know you have over-fitment if you have a large percentage of your dataset as support vectors. The soft-margin SVM allows for some "wiggle room" with separation.
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