Svc.py -

: Generating reports to check for overfitting (requires reducing polynomial degree) or underfitting (requires increasing degree). Key Areas to Check During Your Review

: Using sklearn.svm.SVC for classification.

: Importing data (e.g., from CSV or JSON) and cleaning text by removing stop words and handling n-grams to improve accuracy.

: Ensure the model uses class_weight='balanced' if your dataset has an uneven number of positive and negative samples.

: 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: