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:

1. Feature Engineering: Mapped out features that could be useful in predicting an habit completion and filtered out noise features
2. Created a synthetic dataset for the ML training using Logistic Regression and Decision Tree (Both seemed to work well tho).
3. I tested the ML model with the training dataset and did a mini visual evaluation on the model accuracy and features dependency.