Sentence examples for a generating feature from inspiring English sources

The phrase "a generating feature" is correct and usable in written English.
It can be used to describe a characteristic or element that produces or creates something, often in a technical or scientific context.
Example: "The new software includes a generating feature that allows users to create custom reports effortlessly."
Alternatives: "a producing element" or "a creation attribute".

Exact(1)

Such scale-invariance of correlations is characteristic of multiplicative cascade processes and suggests the existence of a scale independent mechanism which is a generating feature for multiplicative cascades [21], examples of which include hydrodynamic turbulence [7] or the financial stock market [12].

Similar(59)

If so, Facebook is directly linking its behavioral nudging of users, via Safety Check, with a revenue generating feature that will let it take a cut of any money raised to help victims of the same tragedies.

FabKids makes it easy to skip a month, and has also set up another revenue generating feature via an option which allows friends and family to "gift" an outfit from the site with no further commitment.

For languages where word boundaries are not readily identified in text, word segmentation is a key first step to generating features for an NER system.

The other advantage is that a predictor generates feature elements that are often smaller in magnitude than the feature elements generated by a difference operator.

In a first step, a early visual processing stage generates feature maps of vertical, horizontal and diagonal orientations.

This is done in the context of proposing a novel system to identify rotating-machinery faults based on SBM, that is employed either as a standalone classifier or to generate features for a random forest classifier.

Recently, another assembly quality metric has been proposed that uses alignments of paired-end and mate-pair reads to an assembly to generate Feature-Response Curves (FRC) [ 15, 64].

From a machine-learning perspective, most feature generation frameworks use a wrapper approach to evaluate generated features on the training set.

The flexural torsional coupled motion is generated featuring a symmetric lay-up composite configuration.

Firstly, the SIF operation is performed on a sound file to generate features for each segmented frame, which has the same length for analysis [8].

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