Sentence examples similar to an assignment of labels from inspiring English sources

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A proper D2-coloring[21] of G is an assignment of colors, labeled by natural numbers to the nodes in V, such that any pair of nodes within two-hop neighborhood receives different colors.

The result of the DBSCAN clustering is an assignment of a cluster label to each stop, where the label represents the place that the stop belongs to.

Shattering definition: Model f with some parameter vector θ shatters a set of data points (x 1, x 2, …, x n ) if for all assignments of labels to the data points there exists a θ such that the model f makes no error evaluating that set of data points.

In addressing the problem of named entity recognition, we employed a sequence labelling approach which involves the automatic assignment of labels to a given sequence of items, i.e., the ordered tokens in a sentence.

All of which is to say that as a collection show, "An American Legacy" is no less or no more than it should be: a mix of the admirable, the functional and the negligible, with the assignment of labels still very much in process.

The assignment of labels to the word features of test set gradually generates different two branches of decision tree.

On the other hand, in sequence labelling the assignment of labels is such as to satisfy dependencies between sentences.

MAXQDA facilitates data management, the assignment of labels, codes and themes to text fragments and the generation of thematic matrices containing these elements.

A k-labeling of a graph G with n vertices is an assignment of a set l v)⊂{1,2,…,n} to each vertex v of G, such that |l v)|=k and all label sets are distinct.

Given the graph initialization, the propagation algorithm finds an optimal assignment of node labels f v) and f u), which minimizes the objective function Q f = ∑ v, u ∈ E w v, u f v d v - f u d u 2 + μ ∑ v ∈ V f v - y v 2 + ∑ u ∈ U f u - y u 2 where μ is a parameter controlling the relative effect of the two parts of the cost function.

The reason why 100% accuracy can be achieved on 3 of the 1000 permutated data is that the sample size is too small (only 10 samples) and therefore even some random assignment of class labels may coincide with the true class labels with some probability.

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