Sentimental Analysis

Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10186

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DC Field	Value	Language
dc.contributor.author	Gupta, Tripti	-
dc.contributor.author	Kumar, Pankaj [Guided by]	-
dc.date.accessioned	2023-09-30T09:08:45Z	-
dc.date.available	2023-09-30T09:08:45Z	-
dc.date.issued	2023	-
dc.identifier.uri	http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10186	-
dc.description	Enrollment No. 191346, 191506	en_US
dc.description.abstract	An approach called SMOTE (Synthetic Minority Over-sampling Technique) was developed to deal with the issue of unbalanced datasets in machine learning. When one class has a disproportionately smaller number of examples than another, the datasets are imbalanced, which makes it challenging for machine learning models to correctly forecast the minority class.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Jaypee University of Information Technology, Solan, H.P.	en_US
dc.subject	Sentiment analysis	en_US
dc.subject	Natural language processing	en_US
dc.subject	Encoder	en_US
dc.subject	Decoder	en_US
dc.title	Sentimental Analysis	en_US
dc.type	Project Report	en_US
Appears in Collections:	B.Tech. Project Reports

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