Titlebook: Machine Learning for Econometrics and Related Topics; Vladik Kreinovich,Songsak Sriboonchitta,Woraphon Y Book 2024 The Editor(s) (if appli

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,Forecasting Market Index of Stock Exchange of Thailand, Malaysia, and Singapore with the Gaussian P markets. This study compares the forecasting performance of the models with a lag from 1 to 5. The comparison is based on the root-mean-square error (RMSE) and the mean absolute error (MAE). The prediction results from the GPR are then compared to the Autoregressive model (AR). The results show tha

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,Why Rectified Linear Unit Is Efficient in Machine Learning: One More Explanation,ion for why rectified linear units—the main units of deep learning—are so effective. This explanation is similar to the usual explanation of why Gaussian (normal) distributions are ubiquitous—namely, it is based on an appropriate limit theorem.

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,Why Shapley Value and Its Variants Are Useful in Machine Learning (and in Other Applications),rative games). This success is somewhat puzzling, since the usual derivation of the Shapley value is based on requirements like additivity that are natural in cooperative games and but not in machine learning. In this paper, we provide a new simple derivation of the Shapley value, a derivation that

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,Household Characteristics and the Pattern of Gambling, Alcohol and Tobacco Expenditures,these behaviors have been found to be interrelated. This study illustrates the pattern of the unhealthy behaviors in Thailand by clustering households based on their gambling, alcohol and tobacco expenditures using the k-mean clustering method. In addition, we also examine household characteristics