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dc.contributor.authorYadav, Arun-
dc.contributor.authorRay, Arjun (Advisor)-
dc.date.accessioned2024-05-13T11:29:44Z-
dc.date.available2024-05-13T11:29:44Z-
dc.date.issued2023-11-29-
dc.identifier.urihttp://repository.iiitd.edu.in/xmlui/handle/123456789/1450-
dc.description.abstractThis report presents a comprehensive analysis of revenue forecasting methods employed in the context of the hotel industry or business. The primary objective is to assess the effectiveness of various machine learning models to predict more data and try to get higher accuracy, including linear regression, decision trees, robust models, and the Prophet model developed by Facebook for time series data. The forecasting horizon contains 21 days with a bucket of 7 days.en_US
dc.language.isoen_USen_US
dc.publisherIIIT-Delhien_US
dc.subjectProblems in ml modelen_US
dc.subjectTraining and testing of dataseten_US
dc.subjectPrediction and Accuracyen_US
dc.subjectForecast Report Reporten_US
dc.subjectFuture Scopeen_US
dc.titleDevelopment of a forecasting tool utilizing ML techniquesen_US
dc.typeOtheren_US
Appears in Collections:Year-2023

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