Regression trees for hospitality data analysis

Tsionas, Mike G.; Assaf, A. George

doi:10.1108/ijchm-06-2022-0705

Cited by 2 publications

(1 citation statement)

References 33 publications

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“…A regression tree (RT) is a nonparametric machine learning method and predictive modelling approach that does not require the normalization or scaling of data. This method can be used with many different functional forms [38]. An RT is a supervised learning-based nonlinear model.…”

Section: Rt Machine Learning-based Approachesmentioning

confidence: 99%

Validation of Instruments for the Improvement of Interprofessional Education through Educational Management: An Internet of Things (IoT)-Based Machine Learning Approach

Mohamed,

Altinay,

Altinay

et al. 2023

Sustainability

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Educational management is the combination of human and material resources that supervises, plans, and responsibly executes an educational system with outcomes and consequences. However, when seeking improvements in interprofessional education and collaborative practice through the management of health professions, educational modules face significant obstacles and challenges. The primary goal of this study was to analyse data collected from discussion sessions and feedback from respondents concerning interprofessional education (IPE) management modules. Thus, this study used an explanatory and descriptive design to obtain responses from the selected group via a self-administered questionnaire and semi-structured interviews, and the results were limited to averages, i.e., frequency distributions and summary statistics. The results of this study reflect the positive responses from both subgroups and strongly support the further implementation of IPE in various aspects and continuing to improve and develop it. Four different artificial intelligence (AI) techniques were used to model interprofessional education improvement through educational management, using 20 questions from the questionnaire as the variables (19 input variables and 1 output variable). The modelling performance of the nonlinear and linear models could reliably predict the output in both the calibration and validation phases when considering the four performance metrics. These models were shown to be reliable tools for evaluating and modelling interprofessional education through educational management. Gaussian process regression (GPR) outperformed all the models in both the training and validation stages.

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Section: Rt Machine Learning-based Approachesmentioning

confidence: 99%

Validation of Instruments for the Improvement of Interprofessional Education through Educational Management: An Internet of Things (IoT)-Based Machine Learning Approach

Mohamed,

Altinay,

Altinay

et al. 2023

Sustainability

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Reflecting on the contributions of Professor Tsionas in time series analysis, asset price modelling, and forecasting

Mamatzakis

2024

Tourism Economics

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While Professor Tsionas is widely acclaimed for his ground-breaking works in Bayesian panel econometrics and frontier analysis models, his substantial impact in time series analysis in finance remains relatively less known. Nonetheless, the doctoral thesis of Professor Tsionas focussed on asset pricing models, serving as a foundation for his subsequent research pursuits in time series analysis and forecasting. Characterised by elegance and simplicity, Professor Tsionas conceptualised econometric models and Bayesian estimation methods that have been applied to fields such as banking, finance, macro-finance, and tourism. In addition, his insights into time series analysis have informed decision-making processes in these fields.

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Regression trees for hospitality data analysis

Cited by 2 publications

References 33 publications

Validation of Instruments for the Improvement of Interprofessional Education through Educational Management: An Internet of Things (IoT)-Based Machine Learning Approach

Validation of Instruments for the Improvement of Interprofessional Education through Educational Management: An Internet of Things (IoT)-Based Machine Learning Approach

Reflecting on the contributions of Professor Tsionas in time series analysis, asset price modelling, and forecasting

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