It balances the trade-off between maximizing the margin and minimizing classification error
It sets the learning rate
Questions & Step-by-Step Solutions
What role does the 'C' parameter play in SVM?
Step 1: Understand that SVM stands for Support Vector Machine, which is a type of machine learning model used for classification tasks.
Step 2: The 'C' parameter is a setting in SVM that helps determine how strict the model should be about classifying data points correctly.
Step 3: A small 'C' value means the model will allow some misclassifications to create a wider margin between different classes.
Step 4: A large 'C' value means the model will try very hard to classify all data points correctly, even if it results in a narrower margin.
Step 5: Therefore, 'C' controls the balance between having a wide margin (which can lead to better generalization) and having fewer classification errors (which can lead to overfitting).
