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Examining Psychedelics Use and Mental Health Conditions: Supervised Learning

Thinkful Supervised Learning Capstone Project:

Examining Psychedelics Use and Mental Health Conditions

Google Slides presentation: https://bit.ly/LG-PsychedelicMHCs

An examination in publically-available raw data regarding psychedelics use in US citizens, 2020

Objective: predicting psychedelics use based on certain mental health conditions and/or recent prior knowledge of psychedelic therapeutic use

Google Colab Python notebook code

Conclusions:

  • Can predict with 85% accuracy that those with certain mental health conditions AND prior knowledge of psychedelics-as-therapeutic-tool are using psychedelics
  • Establishes connection between recreational use as form of self-medicated mental health care
  • Connection between psychedelics and mental health care can advance science about:
    • how these compounds work in relation to mental health
    • how to use them safely
    • how to regulate and optimize

Data Analysis:

DATA SOURCE: Psychedelic Mushrooms in the USA: Knowledge, Patterns of Use, and Association With Health Outcomes


Downloadable raw data set


My analysis included:
  • Comprehensive EDA
  • Hypothesis/Objective formation
  • Imbalanced data mitigation:
    • random manual sample generation
    • SMOTE synthetic resampling
    • ROS/RUS synthetic resampling
    • Tomeks/NearMiss synthetic resampling
  • Feature engineering
  • Benchmarking
  • General Logistic Regression predictive modelling
  • KNN classification
  • Random Forest classification
  • Penalized SVM/SVC classification
  • Final recommendations based on my findings for further data exploration and industry decisions/progression

December 19, 2022

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