Sentence examples for categorization approaches from inspiring English sources

The aforementioned types of classifications cover a range of NR methods, but there is a need to broaden the categorization approaches in order to review currently existing methods in this area.

Further, there is variability in categorization approaches amongst studies that dichotomize into positive and negative groups.

Different categorization approaches may have modified specific study findings and conclusions.

Dictionary-based categorization approaches attempt to exploit lexical similarities between GO terms (descriptions and synonyms) and the input text to be categorized.

The potential ramifications of each source of uncertainty should be addressed and some crude classification or categorization approaches could be developed (e.g., low, intermediate, or high uncertainty) with respect to a given source.

In [28] Schultz et al. proposed a hashtag-based categorization approach in order to test the applicability of several machine learning techniques in conjunction with relevant feature selection algorithms for the text categorization problem.

Essock and colleagues (Essock, Sinai, McCarley, Krebs, & DeFord, 1999; Essock et al., 2004) took a categorization approach to their tasks, asking participants to classify whether stimuli represented imagery types with content such as sky, trees, buildings, and water.

We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms.

This categorization was done by looking for specific keywords within the first few words of the description, and since there is no controlled vocabulary the accuracy of this categorization approach was validated by random sampling and manual examination (see Methods).

In conclusion, this study shows that a bottom-up, categorization approach combining the IBS method and hierarchical cluster analysis can detect subgroups of subjects based on phenotypes that are associated with β2-AR gene polymorphisms.

Furthermore, a categorization approach assumes that the threshold values are intractable, when commentary has begun to suggest that the reference ranges for optimal benefit may be too low [27] and depend on the disease or population characteristics being studied.