Sentence examples for empirical classification was from inspiring English sources

The empirical classification was best predicted by environmental variables.

Indeed, the empirical classification was specifically developed for studies related to global change across the U.S. (Costanza et al. 2017).

We also excluded plots labeled with FIA forest type groups "Exotic Hardwoods" or "Exotic Softwoods" because the empirical classification was based on native U.S. species only.

The empirical classification was predicted best by environmental variables, and, along with the FIA classification, was highly related to a set of environmental variables measured at a range of scales.

Because the empirical classification did not explicitly incorporate environmental conditions, and because the USNVC classification is based in part on environmental conditions and ecological settings, it is somewhat surprising that prediction of the empirical classification was best.

A second reason for the relatively strong performance of the random forest model for predicting the empirical classification is the fact that the empirical classification was developed based on similarities among plots in recent forest inventory data (Costanza et al. 2017).

The empirical classification is hierarchical, and any level of the hierarchy with any number of clusters can be chosen to fit the objectives of a given study.

This empirical classification is an objective approach to variable construction and can be generally applied across Norwegian hospitals.

The empirical classification is an objective approach to variable construction and can be generalized to the population of Norwegian hospitals, e.g. when comparing patient and quality-of-care outcomes across different organizational models.

A combination of curve-fitting, zonation algorithms, and empirical classification techniques are used to show that, although the long profile of the Lower Mississippi River is concave at the largest scale, the profile is characterised by discontinuities, shorter trends and zonal variations in the amplitude and wavelength of pool crossing morphology.

Therefore, when the aim is to relate forest community types across broad extents to climate or environmental characteristics, the empirical classification may be best.