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In this study, we present a computational model of a car driver's cognitive process and eye movement in relation to risk evaluation for greater safe driving assistance. The model status is mainly determined by visual inputs. In simulations, we reconstructed and predicted the driver eye movements while driving using an environmental risk calculation model, and compared them to the eye movements of...
Concept drift, the change over time of the statistical properties of the target variable, is a serious problem for online learning systems. To overcome this problem, we propose a method inspired by human behavior for detecting sudden concept drift. We first conducted a human behavior experiment to investigate our working hypothesis that humans can detect changes quickly when their confident classifications...
This paper presents a quick machine learning system inspired by human learning behavior. Data-mining systems based on machine-learning usually need a large number of iterations to acquire correct solutions, whereas people usually find appropriate hidden rules after only a small number of observations of the instances in a dataset. We think that this quick learning is the result of using tentative...
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