• Himanshu Kumar Singh
• Dr Shailendra Narayan Singh

Abstract: Machine learning offers leverage for creating appropriate predictions that outline the domain's decisive frameworks in a world driven by data and decision-making predicted by the captured data of the domain. The consumer and the decision they make that leads to a successful operation or a cancellation are the lifeblood of the hotel sector. In this work, a number of machine learning classification algorithms were implemented in order to compare their performance metrics and identify the necessary features. The hotel business was chosen since it is the most lucrative and fast-paced in order to collect data from past operations and other pertinent factors to determine if a reservation will be successful or canceled.

Keywords: Exploratory Data Analysis, Gradient Descent, Random Forest, XGBoost, LGBM, Adaboost, Accuracy, Precision, Recall, F1-Score, and Support

"Comparative analysis of classification algorithms for the hospitality industry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.d58-d65, May-2023, Available :http://www.jetir.org/papers/JETIR2305314.pdf

"Comparative analysis of classification algorithms for the hospitality industry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppd58-d65, May-2023, Available at : http://www.jetir.org/papers/JETIR2305314.pdf