A supervised machine learning approach to predict vulnerability to drug addiction

A supervised machine learning approach to predict vulnerability to drug addiction

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Bibliographische Detailangaben
Hauptverfasser:	Faisal, Fahim, Shahriar, Arif, Mahmud, Sohan Uddin, Shuvo, Rakibul Alam
Weitere Verfasser:	Chakrabarty, Amitabha
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2020
Schlagworte:	Primary data mRMR Deep beilief nerwork Reliability Vulnerability to addiction Neural network Random forest Neural networks (Computer science) Machine learning
Online Zugang:	http://hdl.handle.net/10361/13779

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