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Locally weighted learning (LWL) is a form of lazy learning and focuses on locally weighted regression. Due to its high efficiency and flexibility, the learning mechanism is widely used in prediction. However, LWL fails when the data points are sparse, and fewer survey concerns about tuning fit parameters in local model with density of the data input. This paper discusses the relationship between data...