"discrete features" is a perfectly correct and usable phrase in written English.
You can use it to refer to individual, distinct components or elements that are separate from one another. For example, "The software program was designed to organize and analyze data based on its discrete features."
The aim was to subvert the traditional conception of the gallery, 'dissolving the discrete features of the white cube architecture'.
Clouds have a specific definition, he added: "discrete features that are optically thick and therefore would block the surface below them".
Thermal cycling experiments with proteins show, in addition to random features, also discrete features.
It is also commonly used to investigate discrete features, such as an expanding mine, construction site, or a linear feature that requires precise delineation.
Both theoretical and experimental comparisons with other representative filter approaches on UCI datasets show that the proposed algorithm is effective for selecting continuous and discrete features, as well as the mixture of continuous and discrete features.
The time resolved PL-spectra exhibit several discrete features, which are not pronounced in steady state PL spectra.
The fault was explicitly represented as a discrete feature and the surrounding rock was treated as a dual-continuum (fracture matrix) system.
They intersect a stimulated reservoir region, which is modeled using a dual-permeability approach, as well as a wide-aperture zone, which is incorporated as a discrete feature.
In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition.
Given the parallel and discrete feature of EC activities and the tacit/explicit status variation of intellectual content, a modeling approach based on improved Petri net is proposed for the knowledge flow in EC process.
This paper introduces a novel approach that can measure the correlation between a continuous and a discrete feature, and then proposes an efficient filter feature selection algorithm based on correlation analysis by removing weakly relevant and irrelevant features, as well as relevant but redundant features.
