Machine learning project: understanding hospitality as a competitive differential in restaurant management
DOI:
https://doi.org/10.5585/gep.v11i3.18748Keywords:
Software Design, Naïve Bayes, Machine Learning, Hospitality in Service Competitiveness, Food and Beverage ManagementAbstract
The aim of this article is to present the development of a Machine Learning project to predict the classification of the customer in relation to the restaurant, thus enabling the use of Hospitality as a competitive differential. To achieve the objective, a Machine Learning project was developed, which involved the development of a script in the R language, which allows analysis and application in Restaurants, in order to support managers in decision-making and eventual actions to mitigate problems. In order to capture the experts' experience, a model was developed by applying the Naïve Bayes algorithm, which was trained using data obtained from the TripAdvisor Site, reaching a hit rate of around 84% with the test data. This value is acceptable for new analyzes with data from customer opinions, thus demonstrating that the project has achieved its objective.
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