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Personality traits and drug consumption : a story told by data

Author: Elaine FehrmanVincent EganAlexander N GorbanJeremy LevesleyEvgeny M MirkesAll authors
Publisher: Cham, Switzerland : Springer, [2019] ©2019
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs. After reviewing published works on the psychological profiles of drug users and describing the data mining and machine learning methods used, it demonstrates that the personality traits (five factor model, impulsivity, and sensation  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Elaine Fehrman; Vincent Egan; Alexander N Gorban; Jeremy Levesley; Evgeny M Mirkes; Awaz K Muhammad
ISBN: 9783030104429 3030104427
OCLC Number: 1099434599
Description: 1 online resource
Contents: Intro; Contents; 1 Introduction; References; 2 Drug Use and Personality Profiles; 2.1 Definitions of Drugs and Drug Usage; 2.2 Personality Traits; 2.3 How Many Inputs Do the Predictive Models Have: 5, 30, 60, or 240?; 2.4 The Problem of the Relationship Between Personality Traits and Drug Consumption; 2.5 New Data Set Open for Use; 2.6 First Results in Brief; References; 3 Methods of Data Analysis; 3.1 Preprocessing; 3.1.1 Descriptive Statistics: Mean, Variance, Covariance, Correlation, Information Gain; 3.1.2 Input Feature Normalisation; 3.2 Input Feature Transformation 3.2.1 Principal Component Analysis-PCA3.2.2 Quantification of Categorical Input Variables; 3.2.3 Input Feature Ranking; 3.3 Classification and Risk Evaluation; 3.3.1 Single Attribute Predictors; 3.3.2 Criterion for Selecting the Best Method; 3.3.3 Linear Discriminant Analysis (LDA); 3.3.4 Logistic Regression (LR); 3.3.5 k-Nearest Neighbours (kNN); 3.3.6 Decision Tree (DT); 3.3.7 Random Forest (RF); 3.3.8 Gaussian Mixture (GM); 3.3.9 Probability Density Function Estimation (PDFE); 3.3.10 Naïve Bayes (NB); 3.4 Visualisation on the Nonlinear PC Canvas: Elastic Maps; References 4 Results of Data Analysis4.1 Descriptive Statistics and Psychological Profile of Illicit Drug Users; 4.2 Distribution of Number of Drugs Used; 4.3 Sample Mean and Population Norm; 4.4 Deviation of the Groups of Drug Users from the Sample Mean; 4.5 Significant Differences Between Groups of Drug Users and Non-users; 4.6 Correlation Between Usage of Different Drugs; 4.7 Ranking of Input Features; 4.8 Selection of the Best Classifiers for the Decade-Based Classification Problem; 4.9 Correlation Pleiades of Drugs; 4.10 Overoptimism Problem 4.11 User/Non-user Classification by Linear Discriminant for Ecstasy and Heroin4.12 Separation of Heroin Users from Ecstasy Users: What Is the Difference?; 4.13 Significant Difference Between Benzodiazepines, Ecstasy, and Heroin; 4.14 A Tree of Linear Discriminants: No Essential Improvements; 4.15 Visualisation on Nonlinear PCA Canvas; 4.16 Risk Maps; References; 5 Summary; References; 6 Discussion; References; A Main Tables; A.1 Psychological Profiles of Drug Users and Non-users; A.2 Correlation Between Consumption of Different Drugs; A.3 Linear Discriminants for User/Non-user Separation
Responsibility: Elaine Fehrman, Vincent Egan, Alexander N. Gorban, Jeremy Levesley, Evgeny M. Mirkes and Awaz K. Muhammad.

Abstract:

This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs.  Read more...

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