Automated Expense Categorization with Machine Learning #599
Description
Description:
Enhance the existing AI categorization by implementing a more advanced ML model that learns from user corrections, automatically categorizes new expenses with higher accuracy, and suggests category improvements. This builds on the current categorization service to make it smarter over time.
Proposed Plan:
Extend services/categorizationService.js to include ML training capabilities using libraries like Brain.js or integrate with a cloud ML service.
Add a feedback loop where users can confirm/correct categorizations, feeding back into the model.
Create a new model file (e.g., models/CategoryModel.js) to store training data.
Update the expense input form to show suggested categories and allow corrections.
Implement periodic retraining of the model using cron jobs in services/cronJobs.js.
Add analytics to track categorization accuracy and improve the model.