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• W4283370355 abstract "In this paper, we propose an interval local linear method (ILLM) to fit the regression model with interval-valued explanatory and response variables. The proposed method has no restriction on the form of the regression function. Moreover, it reduces the boundary effect of interval kernel method. Some experimental studies including two simulations and four real datasets are examined to evaluate the proposed method. Experimental results show that our method has higher predictive accuracy than some existed methods, including the center and range method, the interval least absolute method, the interval kernel method, multi-output support vector regression and the interval multilayer perceptron." @default.
• W4283370355 created "2022-06-25" @default.
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• W4283370355 date "2022-08-01" @default.
• W4283370355 modified "2023-10-14" @default.
• W4283370355 title "Nonparametric regression for interval-valued data based on local linear smoothing approach" @default.
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• W4283370355 doi "https://doi.org/10.1016/j.neucom.2022.06.073" @default.
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