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Classification of Addiction Behavior based on Regular and Rare Model

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Title Classification of Addiction Behavior based on Regular and Rare Model
 
Creator Sabapathi, V
Peter, J Selvin Paul
 
Subject Addictive preventive
Introspective system
Predictive model
Substance addiction
Virtual addiction
 
Description 593-599
Realization is the comprehension of existence in its widest terms. Many of us, both physically and virtually, are
unconscious of our level of addictive concern. Predicting virtual and emotional-based activity poses certain difficulties in
determining an addiction level. Specifically, how to compute the addictive and what types of controls can help us monitor
the addiction and get a good estimate of the individual's addicted stage. The threshold levels vary depending on a variety of
factors such as age, gender, society, and so on. The addiction mentality system's prediction plays a vital role. In this regard,
our research develops a Regular and Rare (RAR) based classification model for finding effective addiction predictors. This
RAR classification and prediction technique is based on an examination of addiction patterns' consistency. This strategy
focuses on the length of time spent doing the same activity rather than the amount of quantity consumed. The concept
behind it if an individual consumes a low density of nicotine but persists for a decade, this is considered as a habitual and
addictive activity. In such a way that if an individual doesn't really engage in the very same type of activity for an extended
period of time, the action may be considered an uncommon occurrences rather than an addictive class.
 
Date 2021-09-01T09:41:13Z
2021-09-01T09:41:13Z
2021-07
 
Type Article
 
Identifier 0975-1084 (Online); 0022-4456 (Print)
http://nopr.niscair.res.in/handle/123456789/57975
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source JSIR Vol.80(07) [July 2021]