: Generating reports to check for overfitting (requires reducing polynomial degree) or underfitting (requires increasing degree). Key Areas to Check During Your Review
: Check if the data is properly divided into training, validation, and test sets to ensure the model's reliability on new data. svc.py
: Adhere to the PEP8 style guide —for instance, avoid using lower-case 'l' as a variable name to prevent confusion with the number '1'. Other Possible Contexts Depending on your project, svc.py might instead refer to: : Generating reports to check for overfitting (requires
: Ensure the model uses class_weight='balanced' if your dataset has an uneven number of positive and negative samples. svc.py