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

Practice Questions

Q1
What is the role of the regularization parameter 'C' in SVM?
  1. To control the complexity of the model
  2. To determine the type of kernel used
  3. To set the number of support vectors
  4. To adjust the learning rate

Questions & Step-by-Step Solutions

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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