The phrase "a given weighted" is not correct in standard written English.
It may be intended to refer to a specific weighted value or concept, but it lacks clarity and proper grammatical structure.
Example: "In the analysis, we will consider a given weighted average to determine the overall performance."
Alternatives: "a specific weighted" or "a particular weighted".
Degree centrality of each node/concept, in a given weighted and directed graph, is defined as the sum of the absolute values of the weights of the outgoing and incoming edges [ 8, 95].
In the final section, we consider the compact perturbation of finite summations of a given weighted composition operator.
To prove the correctness of the above algorithms, we need the following lemma: For a given weighted digraph G, and sets of seeds S o and S b, such that S o ={s i }, we have that ({varepsilon }_{infty downarrow }^{{in}} = V_{{b}}(s_{i})), and ({varepsilon }_{infty downarrow }^{out} = V_{{b}}^{not parallel }(s_{i})).
Our algorithm, DME, extracts all densely connected modules from a given weighted interaction network.
For a given weight vector, the weighted sum rate maximization we then need to solve reads as max r w T r s. t. r ∈ C OB. (6).
For this reason, we use information on all respondents giving the full interview in a given year weighted with cross-sectional weights available in the BHPS that adjust for inclusion of new entrants and for within household nonresponse.
In this paper we present a cycle detection based greedy algorithm, to obtain a minimal spanning tree of a given input weighted undirected graph.
We present a directed search algorithm, called K⁎, for finding the k shortest paths between a designated pair of vertices in a given directed weighted graph.
Therefore, we used a measurement that takes into consideration the sum of the qualities of all clusters provided by a given method, weighted by the variation in the quality of clusters.
For a given tree U (weighted or not), consider the two following properties on U: Property ONLY-NAD: U has no AD vertices; Property ONLY-AD: U is rooted at an AD vertex and contains no NAD vertex.
The false positives and false negatives from these error analyses were caused by unbalanced feature weights and training examples, lack of training examples for a given feature (low weighted feature) and missing features.
