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http://repository.iiitd.edu.in/xmlui/handle/123456789/1450Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yadav, Arun | - |
| dc.contributor.author | Ray, Arjun (Advisor) | - |
| dc.date.accessioned | 2024-05-13T11:29:44Z | - |
| dc.date.available | 2024-05-13T11:29:44Z | - |
| dc.date.issued | 2023-11-29 | - |
| dc.identifier.uri | http://repository.iiitd.edu.in/xmlui/handle/123456789/1450 | - |
| dc.description.abstract | This 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.iso | en_US | en_US |
| dc.publisher | IIIT-Delhi | en_US |
| dc.subject | Problems in ml model | en_US |
| dc.subject | Training and testing of dataset | en_US |
| dc.subject | Prediction and Accuracy | en_US |
| dc.subject | Forecast Report Report | en_US |
| dc.subject | Future Scope | en_US |
| dc.title | Development of a forecasting tool utilizing ML techniques | en_US |
| dc.type | Other | en_US |
| Appears in Collections: | Year-2023 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| BTP_Report_2020033 - Arun Yadav.pdf Restricted Access | 139.12 kB | Adobe PDF | View/Open Request a copy |
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