Svc.py -

: Check if the data is properly divided into training, validation, and test sets to ensure the model's reliability on new data.

: Using sklearn.svm.SVC for classification. svc.py

A well-structured svc.py usually includes the following stages: : Check if the data is properly divided

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

When reviewing this script, consider these specific technical aspects:

: For large datasets, LinearSVC is often preferred over SVC because it is less computationally expensive and converges faster.