Interpretable Models for Understanding Immersive Simulations
IJCAI 2020, pp. 2319-2325, 2020.
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This paper describes methods for comparative evaluation of the interpretability of models of high dimensional time series data inferred by unsupervised machine learning algorithms. The time series data used in this investigation were logs from an immersive simulation like those commonly used in education and healthcare training. The struc...More
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