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It is important to mention that measuring intensity of training by self-reported accounts of number of hours might be prone to measurement error, which in turn might affect our estimated training impacts.
An interesting treatment of the above problem can also be found in Jankowski and Grabczewski (2009), where the authors propose to take into account not only the expected performance of the algorithm but also its estimated training time.
In this way the algorithms can be ordered according to the estimated training complexity, which allows to produce relatively well-performing models very quickly and then look for better solutions, while the ones already trained are producing predictions.
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In addition to measuring cardiorespiratory fitness/VO2peak, it also serves as a medical evaluation, and maximal heart rate is used to estimate training intensity for women participating in the exercise programme.
Our findings suggest that it is also important for therapists or practitioners to assess general cognitive function in order to estimate training ability at baseline and adjust their approach to exercise.
Our findings suggest that it is important for therapists and health care practitioners to assess general cognitive function in order to estimate training ability at baseline and adjust their approach to exercise.
The model also allows for studying the tradeoff between distance and volume, the impact of using aggregated models for estimating train transportation cost and carbon emissions as well as the potential policy measures that enable aligning cost and carbon emissions.
But because that system uses a computer program to estimate train movements based on a set schedule, it can sometimes be wrong — when, for instance, a train is held in a station because of a mechanical problem or an ill passenger.
Allotta et al. [6] developed an algorithm to correct the wheel slip when using wheel rotational speed to estimate train position between automatic train protection balises.
However, in practice, the channel vectors are estimated from training sequences and, inherently, this leads to imperfect estimation.
A statistical model of prostate is estimated from training set of manually delineated images.
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