I have multiple features and I want to predict three outcome scores.
Features:
- Length in cm smallest is 40cm biggest is 209cm
- Kilo: 39 till 302
- Age: 19 till 111
- Gender: Male, female, transgender
- Diagnoses: numbers of different diseases
- Medicines: numbers of different medicines
- Urine level: 0 till 5
Scores:
- Scale of Happy 1 till 7
- Scale of depression 1 till 7
- Scale of health 1 till 7
I know I can use supervised learning and create models where I predict the scores individually. I already pre-trained three different models.
Do you have some feedback?
Happiness, depression and health are related. Are there algorithms that can deal with this? Based on historical data (the features and predictions) and the trained model I want to predict the scores for new patients based on their features and historical scores.