: Importing data (e.g., from CSV or JSON) and cleaning text by removing stop words and handling n-grams to improve accuracy.
: Check if the data is properly divided into training, validation, and test sets to ensure the model's reliability on new data.
A well-structured svc.py usually includes the following stages:
: Using sklearn.svm.SVC for classification.