Rudimentary feedback based on decision tree

[sjkar3]

Create some rudimentary feedback on sleep quality based on this decision tree: https://github.com/ks-wang/association-analysis-and-regression-model?tab=readme-ov-file#decision-tree

This will require adding more data collection from user.

When providing feedback, should look at what possible changes to the users' data would make the biggest difference (e.g. if they were at the bottom of the decision tree where it forks based on alcohol consumption < 0.5 and they drank to get a result of fair, not drinking would've given them a result of excellent and should be the suggestion)

[sjkar3]

Data required:

• Sleep duration (already captured)
• Awakenings
• Age
• Alcohol consumption

[sjkar3]

NB: Alcohol consumption is in oz of alcohol / pure ethanol consumed in previous 24 hours 1 oz is approx 3 standard drinks We should convert this into standard drinks

[sjkar3]

Based off this dataset: https://www.kaggle.com/datasets/equilibriumm/sleep-efficiency

[sjkar3]

Requirements:

• add age / birth date question to sign in, store in database for user
• when user starts timer, ask them how many standard drinks they consumed in past 24 hours
• when user ends timer, end timer immediately but ask them for number of awakenings
• after this, provide feedback as per below screenshot (say how good their sleep was, and then list possible ways of improving sleep)