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dc.contributor.advisorArif, Hossain
dc.contributor.authorShihab, Ibne Farabi
dc.contributor.authorOishi, Maliha Moonwara
dc.date.accessioned2018-12-03T09:41:21Z
dc.date.available2018-12-03T09:41:21Z
dc.date.copyright2018
dc.date.issued2018
dc.identifier.otherID 14201002
dc.identifier.otherID 14301011
dc.identifier.urihttp://hdl.handle.net/10361/10951
dc.descriptionThis thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 45-47).
dc.description.abstractA restaurant business is a very prospective and profitable business nowadays. However, ensuring quality food, good stuff, inner-environment etc. is a big concern and most importantly before facing all these, the trickiest part is to choose a perfect place where a restaurant business will flourish. Without doing a perfect research on this area, setting up a restaurant may lead to an immediate downfall. Not only for choosing a preferred restaurant location, people are now hiring professionals to do ground check and here the data scientists are coming into play as a bigshot. This research is focused on suggesting a suitable place for setting up a restaurant business based on the existing data from Yelp where 75 features have been extracted for analysis. Several machine learning algorithms (Support Vector Machine, Decision Tree, Logistic Regression and Decision Tree with presort) have been used and juxtaposed to nurture out the suitable one. As yelp’s review is authentic and it is maintained regularly, we have considered the rating of a business as the point of suggestion. We have also looked at the comparative analysis of this algorithm and searched for an algorithm which gives us the best result.en_US
dc.description.statementofresponsibilityIbne Farabi Shihab
dc.description.statementofresponsibilityMaliha Moonwara Oishi
dc.format.extent47 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectVector Machineen_US
dc.subjectDecision Treeen_US
dc.subjectLogistic regressionen_US
dc.subjectRestauranten_US
dc.subjectGeographical locationen_US
dc.subject.lcshMachine learning
dc.subject.lcshData mining
dc.titleWhere will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishmenten_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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