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However, as these technologies evolve, the range of potential applications will continue to expand, as will the thinking regarding how the resultant datasets can be interpreted.
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Natural language generation and automated narrative creation mean that one dataset can be interpreted in multiple ways, giving each targeted audience segment precisely what they need to know, without any confusing background noise.
The correlation information among the attributes of a dataset can be interpreted as the total amount of information shared between the attributes.
Therefore, the quantity ( sqrt{{mathrm{Bias}}^2+{widehat{sigma}}_b^2} ), where Bias is the average prediction bias for the validation dataset, can be interpreted as a measure of prediction accuracy at the relevant scale equivalent to the RMSE used for plot-level predictions.
Importantly, hypothesis-free approaches require an appropriate context, i.e. a framework of related prior knowledge, within which an obtained dataset can be interpreted.
Such standards will be essential for generating meaningful digital datasets that can be interpreted and repurposed for many diverse applications.
The simulation results from surveillance and outbreak datasets (Figs. 2– 4) can be interpreted readily in light of the raw NB results discussed above.
The resulting map is mined for relationships between training dataset enrichments in specific units and can be interpreted further by laying additional data on the map not used during the training.
Harvard considers anything/any file that can be interpreted as a dataset.
Methods prediction performance varies considerably from one dataset to another: First, we note the same social media text can be interpreted very differently depending on the choice of a sentiment method.
These datasets were than simplified into basic soil texture classes based on the content of clay, which can be interpreted by the CASA model.
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CEO of Professional Science Editing for Scientists @ prosciediting.com