Aubrey Gress

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Active learning is a crucial method in settings where a human labeling of instances is challenging to obtain. The typical active learning loop builds a model from a few labeled instances, chooses informative unlabeled instances, asks an Oracle (i.e. a human) to label them and then rebuilds the model. Active learning is widely used with much research(More)
In this paper we use machine learning techniques to develop a model for the prediction of the energetic cost of walking on a positive incline while carrying a load given the subjects body composition. Previous studies on prediction of energy cost have failed to incorporate load, incline and body composition simultaneously in their predictive models. By(More)
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