Sentence examples for categorizing data from inspiring English sources

Ho et al. [10] mention two different approaches for categorizing data.

Whilst not restricted OLAP, data mining is a common way of categorizing data by identifying patterns that a data series exhibits.

Vast does an extremely impressive job of finding and categorizing data in the long tail – making it very simple for others to find listings from anywhere on the web.

We provide numerous illustrations of how CTFs let us extract shape from data and also apply CTFs to manifold clustering, the problem of categorizing data points according to their noisy membership in a collection of possibly intersecting smooth submanifolds of Euclidean space.

A potential problem with categorizing data based on endemism is that we may be falsely classifying cosmopolitan genera as endemic because occurrences outside of the focal region have not been entered into the PaleoDB.

Conventional approach for data analysis was implemented; no structure was used for categorizing data.

Local density of points is ranked and analyzed to categorize data.

This article has categorized data centric misbehaviour detection schemes based on their tendency for malicious information.

Classifiers are used to categorize data, while regression models broadly deal with extrapolating out trends to make predictions.

The categorized data were presented with a table under the two themes: expected instructional objectives and obtained acquisitions.

We categorized data openness into the following four levels: open data, limited open data, permitted open data, and not available (Table 3).