Recreational Drug Consumption and Personality Test Score

Drug consumption dataset from UCI Machine Learning Repositry The goal is to predict whether an individual would be a hard drug user.

Dataset

Description

Database contains records for 1885 respondents. For each respondent 12 attributes are known: Personality measurements and demographic information. All input attributes are originally categorical and are quantified. After quantification values of all input features can be considered as real-valued. In addition, participants were questioned concerning their use of 18 legal and illegal drugs on the last used.

Overview

The dataset is a record of 1885 respondents attributes on:

• Personality measurements:
  • NEO-FFI-R (Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness)
  • BIS-11 (Impulsivity)
  • ImpSS (Sensation Seeking)
• Demographic information:
  • Level of education
  • Age
  • Gender
  • Country of residence
  • Ethnicity
• Self-reported drug consumption on 18 substances + Semeron:
  Alcohol, Amphetamines, Amyl nitrite, Benzodiazepine, Cannabis, Chocolate, Cocaine, Caffeine, Crack, Ecstasy, Heroin, Ketamine, Legal highs, LSD, Methadone, Mushrooms, Nicotine and Volatile substance

and one fictitious drug (Semeron) 0. fdakj

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There are 10,299 observations within the dataset, with training and test set split at 70% / 30%.

Data Visualisation

The jupyter notebook was the code that was used in examining the study,