The phrase "a dataset can be" is correct and usable in written English.
You can use it when discussing the characteristics, properties, or potential uses of a dataset in various contexts, such as data analysis or research.
Example: "A dataset can be used to identify trends and patterns in consumer behavior."
Alternatives: "a dataset may be" or "a dataset is capable of being".
The structure of a dataset can be analysed via the characterisation of blobs, using a number of simple composition and configuration metrics.
N plays a role in assessing the data compressibility since a dataset can be represented on meshes of different refinements.
A dataset can be defined as a collection of related sets of information that can have individual or multidimensional attributes.
Quite often a dataset can be better understood by clustering it in its subspaces, a process called subspace clustering.
The correlation information among the attributes of a dataset can be interpreted as the total amount of information shared between the attributes.
Thus in molecular sciences, the basic object naturally maps to the molecule, since this is the smallest object for which a dataset can be normally be generated and which can usefully be described by its own metadata.
Using this ontology, each attribute in a toxicological dataset can be associated with an entry to the ontology, therefore allowing a unique mapping between endpoints in various and heterogeneous datasets.
In many practically important cases, a massive dataset can be represented as a very large graph with certain attributes associated with its vertices and edges.
Training and optimizing a statistical model on such a large dataset can be extremely time-consuming.
Utilizing these parameters, a SPECT dataset can be converted to a QSPECT dataset allowing quantitation in Becquerels per cubic centimetre or standardized uptake value (SUV).
While Ingrid makes no structural distinction between a dataset and a collection, the DODS mechanism transmits a single dds and das, and Ingrid transmits a set of unique independent variables for netcdf-like clients, so there is a practical limit on how complicated a DODS dataset can be.
