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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)
Regression problems assume every instanceisannotated(labeled)witharealvalue, aformof annotation we call strong guidance. In order for these annotations to be accurate, they must be the result of a precise experiment or measurement. However, in some cases additional weak guidance might be given by imprecise measurements, a domain expert or even crowd(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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