Predicting Movie Ratings at IMDb

Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7486

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DC Field	Value	Language
dc.contributor.author	Lal, Gaurvi	-
dc.contributor.author	Prasher, Anirudh	-
dc.contributor.author	Kumar, Pardeep [Guided by]	-
dc.date.accessioned	2022-10-10T05:25:45Z	-
dc.date.available	2022-10-10T05:25:45Z	-
dc.date.issued	2016	-
dc.identifier.uri	http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7486	-
dc.description.abstract	In this project, we are interested in predicting the movie ratings at IMDb. We apply the predictive data mining techniques of classification and to the database. Among the various attributes of movies like year of release, length (running time), number of votes, and genres, we determine which attributes of a movie affect its rating the most. The prototype model is based on the decision tree (J48) based classification using WEKA 3.7 and Java (Netbeans IDE 8.1)	en_US
dc.language.iso	en	en_US
dc.publisher	Jaypee University of Information Technology, Solan, H.P.	en_US
dc.subject	Movie ratings	en_US
dc.subject	Artificial intelligence	en_US
dc.title	Predicting Movie Ratings at IMDb	en_US
dc.type	Project Report	en_US
Appears in Collections:	B.Tech. Project Reports

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