What is the role of the regularization parameter 'C' in SVM?

What is the role of the regularization parameter 'C' in SVM?

Step 1: Understand that SVM (Support Vector Machine) is a type of machine learning model used for classification tasks.
Step 2: Know that SVM tries to find a line (or hyperplane) that separates different classes in the data.
Step 3: Realize that 'margin' is the distance between the line and the closest data points from each class.
Step 4: Learn that a larger margin is generally better because it means the model is more confident in its predictions.
Step 5: Understand that 'C' is a parameter that controls how much we care about misclassifications (errors) versus the size of the margin.
Step 6: If 'C' is small, the model will prioritize a larger margin, even if it means making more mistakes on the training data.
Step 7: If 'C' is large, the model will focus on minimizing errors, which may result in a smaller margin.
Step 8: Therefore, 'C' helps balance the trade-off between having a wide margin and making fewer mistakes.

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