The phrase "a discrete label" is correct and usable in written English.
It can be used in contexts where you are referring to a distinct or separate identifier, often in fields like data science, programming, or categorization.
Example: "Each category in the dataset is represented by a discrete label that helps in identifying the type of data."
Alternatives: "a distinct label" or "an individual label".
(2) Visualwords, denoted as the discrete set, are formed by clustering the features into N clusters, so that each local feature is assigned to a discrete label.
Visualwords, denoted as the discrete set, are formed by clustering the features into N clusters, so that each local feature is assigned to a discrete label.
The process of discretization typically consists of 3 main steps that are sorting attribute values, finding the cut-point model or discretization scheme of the attributes by iterative splitting or merging, and finally, assigning each value in the attribute with a discrete label corresponding to the interval it falls into.
Disparity estimation is commonly defined as a discrete labeling problem.
This allowed us to convert each column of a PFM to a single discrete label.
Minimizing the above energy with respect to all discrete labels is intractable.
In particular, we introduced a notion of particle [with an associated discrete labeling k, ϵ ( k ) ] given in terms of ladder operators η k.
A set of N training examples of the form (x, y) is given, where y is a discrete class label and x is a vector of d attributes (each of which may be symbolic or numeric).
Finally, we monitored class-specific values for AccuracyC, i.e. the accuracy for the class "structural change", AccuracyN (accuracy for the class "neutral"), CoverageC (coverage for class "change") and CoverageN (coverage neutral) defined by: (2) Our logistic regression model yielded a probability for an instance to be structurally non-neutral rather than a discrete class label.
Slightly different from classifying disease status (discrete label), another family of problems uses tensor neuroimages to predict cognitive outcome (continuous label).
Instead we encode the sequence of blocks with attributes as a graph with discrete labels.
