'C' is a regularization parameter that controls the trade-off between maximizing the margin and minimizing classification error.
Questions & Step-by-step Solutions
1 item
Q
Q: What does the parameter 'C' control in SVM?
Solution: 'C' is a regularization parameter that controls the trade-off between maximizing the margin and minimizing classification error.
Steps: 5
Step 1: Understand that SVM stands for Support Vector Machine, which is a type of machine learning model used for classification tasks.
Step 2: Know that 'C' is a parameter in SVM that helps to control how the model learns from the training data.
Step 3: Realize that 'C' balances two important things: maximizing the margin (the space between different classes) and minimizing classification errors (how many mistakes the model makes).
Step 4: If 'C' is a small value, the model allows some misclassifications to create a wider margin, which can help with generalization to new data.
Step 5: If 'C' is a large value, the model tries to classify all training examples correctly, which can lead to a narrower margin and possibly overfitting.
