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.

Bibliografiska uppgifter
Huvudupphovsmän:	Faisal, Fahim, Shahriar, Arif, Mahmud, Sohan Uddin, Shuvo, Rakibul Alam
Övriga upphovsmän:	Chakrabarty, Amitabha
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2020
Ämnen:	Primary data mRMR Deep beilief nerwork Reliability Vulnerability to addiction Neural network Random forest Neural networks (Computer science) Machine learning
Länkar:	http://hdl.handle.net/10361/13779

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

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