Habit completion predictor
- 1 Devlogs
- 8 Total hours
I'm building an habit completion predictor that predicts whether or not an habit will be completed and learns from users track record overtime
Successfully trained the model with an accuracy of 99% (PSS: That’s because i used synthetic dataset and it wasn’t realistic enough).
What i’ve done so far:
- Feature Engineering: Mapped out features that could be useful in predicting an habit completion and filtered out noise features
- Created a synthetic dataset for the ML training using Logistic Regression and Decision Tree (Both seemed to work well tho).
- I tested the ML model with the training dataset and did a mini visual evaluation on the model accuracy and features dependency.
