• Ashu
• Dr. Leena Singh

In a world driven by data and decision-making predicted by the captured data of the domain, machine learning provides leverage for making suitable predictions that frame the domain’s decisive frameworks. The hospitality industry survives on the customer and the choice that it opts for resulting in a successful operation or a cancellation. In this work, the implementation of various machine learning classification algorithms was performed for the comparative analysis of their performance metrics as well as to discover the necessary features. The hotel industry is the most lucrative and fast-paced and was chosen for data capturing through their history as well as other relevant parameters, predicting a successful operation conversion for predicting a reservation to be successful or cancellation.

Machine Learning; Exploratory Data Analysis; Decision Tree; Random Forest; XGBoost; Gradient Descent; LGBM; Adaboost; Accuracy; Precision; Recall; F1-Score; 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.9, Issue 11, page no.f676-f683, November-2022, Available :http://www.jetir.org/papers/JETIR2211587.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.9, Issue 11, page no. ppf676-f683, November-2022, Available at : http://www.jetir.org/papers/JETIR2211587.pdf