Sentence examples for weight of cluster from inspiring English sources

In the case when the input contains only the weights associated with internal tree branches and lacks any measure of support for entire trees, we use the following equation to calculate the overall cluster weights: (1) W i C = ∑ j = 1 n σ ij × W C ij / n, where W i (C) is the overall weight of cluster i, W(C ij ) is the weight of cluster i in tree j and n is the total number of trees.

Finally, when both cluster and tree initial supports are provided in the input, we use the following equation to infer the overall cluster weight, W i (C, T), for each cluster i: (3) W i C, T = ∑ j = 1 n σ ij × W C ij × W T j / n, where W(C ij ) is the weight of cluster i in tree j, W(T j ) is the support for tree j and n is the total number of trees.

The applied sensitivity analysis, by changing the weight of clusters, indicates that the applied model is stable and capable of being applied for zoning ecotourism sites.

In the above, f k denotes the probability function that specifies the probability that the observation x i is generated from cluster k, π k denotes the weight of this cluster and θ k parameterises the cluster.

where parameter A is the equilibrium difference between the energies of interaction of an SWNT with its surroundings in the solid phase and in the cluster volume, B, the similar difference for SWNTs located on the cluster surface, g n, the statistical weight of a cluster of size n, which depends on both temperature and cluster size n.

Table 2 describes the quality of the cluster fits by the relative weight of each cluster, the number of patients assigned (n) and the mean posterior probability for patients in their assigned clusters.

To avoid excessive weighting of clusters towards the size of the practice, ratio variables were created by dividing the number of nurses by the weighted GP variable, and the number of administration staff by weighted GPs.

Using one of the three equations presented in the section "Inferring weights", the method defines a weight of each cluster based on the weights of the trees containing this cluster and on the cluster's bootstrap scores in these trees.

a The histogram of ligand cluster size, b the target distribution of ligands and ligand clusters, c the ligand (cluster) distribution of targets, d the relationship between the average molecular weight of ligand clusters and the ligand cluster promiscuity, nodes are coloured by the number of the nearby nodes, i.e. node density Fig. 5 The ligand cluster number of HGNC gene family.

The weight of one cluster measures the over-representation of genes within this cluster in a group of functional categories.

The weight of one cluster represents a penalty term which is inversely proportional to the homogeneity between the cluster and the functional categories.