Sentence examples for classification builds from inspiring English sources

The IgD/CD27 classification builds on the notion of CD27 as a universal marker of human memory B cells to distinguish between memory cells (CD27+) and naive B cells (CD27−/IgD+).

If we have a new instance x, supervised classification builds a function γ such that: (1) The chosen algorithms in this article are representative from several paradigms, because it is not known a priori which one is more suitable for this type of data.

The former can be understood as a finer-grained classification built on the latter: nonscalar change motion morphemes are equivalent to Talmy's manner-of-motion morphemes, whereas the other three types are subtypes of Talmy's path morphemes, each with a different scale structure.

A classification built on a set of continually changing parameters is constantly changing and difficult to evaluate.

RF is an ensemble method for classification built from a set of decision trees that grow in randomly selected subspaces of data.

Firstly, the results for each classification built from training datasets are expressed in terms of a classification accuracy rate, which represents the similarity between the pathological clinical diagnosis and the microarray diagnosis [ 14].

The unsupervised classification method built on top of such measures have been shown here to consistently produce phylogenic trees for species genomes as well language classifications built on text documents.

The rapid accumulation of new knowledge about the molecular characteristics of tumors can quickly change classifications built on morphology or molecular biology.

He first described studies from the Børresen-Dale group showing that breast tumor classifications built on levels of genomic distortion have prognostic value [ 14].

A classification algorithm builds a classification model that, based on the values of the predictor attributes for a given data instance, predicts what is the class value for that instance.

The classification approach builds on random forest classification with learning data extracted from higher resolution land cover maps.