International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Prediction of Drug Addiction Using Supervised Learning

Abstract

Drug Addiction is one of the growing threats over the India. There are a lot of differences between a drug- addicted and non-addicted person on health condition, social life, particular life, and domestic life actions. So, steps should be taken to help drug habit with proper restorative issues. In this paper, we dig for the influential factors behind drug addiction and possible results to reduce the drug addiction rate. Utmost of the data of drug- addicted people and for non-addicted person data we've collected from different sources. All men and women aged group of 17 to 45. Our primary data set is constructed of only 200 qualitative data. We have used 5 algorithms that have been deployed including Logistic regression, Decision Tree, Random Forest, Naive Bayes, Support Vector Machine and their results are contrasted.

Country : India

1 Mohan S2 Mrs. Shailaja L K

  1. PG Student of MCA, Dr. Ambedkar Institute of Technology, Bangalore, India
  2. Assistant Professor, Department of MCA, Dr. Ambedkar Institute of Technology, Bangalore, India

IRJIET, Volume 6, Issue 5, May 2022 pp. 213-216

doi.org/10.47001/IRJIET/2022.605030

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