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@article{169977,
        author = {Anjali Dongre and Avdhoot Pawar and Sunil Sangave and Aditya Bansul and Anubhav Pandey and Shriya Deshpande},
        title = {Analysis and Evaluation of Business and Sales},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2920-2977},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169977},
        abstract = {Cancellations in bookings show a negative impact in the hospitality industry field while making management decisions. To prevent the negative impact of the cancellations, a lot of policies are implemented along with a few overbooking techniques, this, in turn, can severely damage the income and reputation of that particular hotel. To prevent this situation, machine learning models have been developed. These models use previous data from the hotel and then get trained to predict whether the specific reservation would be canceled. For this, two hotels, Resort hotel, and City hotel have been considered and then the ML models are used to predict how these specific actions taken by the hotel management have a practical effect on the revenue and cancellations of the hotel. This makes the management think again about policies and their decisions. The ML models will help management in predicting the number of cancellations that may occur.},
        keywords = {Machine Learning, Artificial Intelligence, Power BI, Logistic Regression, Ridge Classifier, SGD Classifier, Random Forest Classifier, Navies Bayes’.},
        month = {November},
        }