Dataset : https://archive.ics.uci.edu/dataset/373/drug+consumption+quantified
Notebook : https://github.com/raacee/project_pda/blob/main/Project_PDA.ipynb
PPT : https://github.com/raacee/project_pda/blob/main/PDA_PPT_DAMECHLI_Racel_CARON_Clement_CORLAY_Anahide.pdf
This project is presented by Clement CARRON, Anahide CORLAY and Racel DAMECHLI
We have selected a dataset on drug consumption and psychological tendencies. The dataset contained data on the individuals' personality scores and their drug consumption. More precisely, the drug features represent the last time someone has used a drug. The personality scores are based on "The Big Five" psychological model. This model has 5 main points :
- conscientiousness (efficient/organized vs. extravagant/careless)
- agreeableness (friendly/compassionate vs. critical/rational)
- neuroticism (sensitive/nervous vs. resilient/confident)
- openness to experience (inventive/curious vs. consistent/cautious)
- extraversion (outgoing/energetic vs. solitary/reserved)
It also had two more points :
- Sensation seekingness
- Impulsivity
Our job on this dataset was to highlight relations that could exist between these substances to a psychological trait, if there was. We then worked to build a machine learning prediction model that could predict the number of illegal drugs someone would have taken throughout their life.
To start the flask app, cd into the pda_api folder and run flask run or if you are using poetry poetry run flask run