Energy distance is a non-negative measure of the distance between distributions that is based on Euclidean distances between random observations, which is zero if and only if the distributions are identical. We use energy distance to measure the statistical distance between two clusters, and search ...
The coefficient M can efficiently be calculated as the sum of the maximum Euclidean distance between two cluster centers and the maximum radius of all clusters. The variables bk∈ {0,1} function as a binary switch: when bk = 0,the constraint is inactivated as the large value of M makes ...
Gap time is a time distance between two clusters on positive and negative sides in PRPD pattern. Seven 6.6 kV motors were investigated by analysing three parameters, the results show that seven motors encountered high, moderate and low PD severity according to amplitude, repetition rate and gap ...
In Fig. 5, a is considered more similar to b than to c because Dab < Dac, where D is the so-called Euclidian distance between a and b. Grouping together of objects with small distances leads to roundish clusters. In Fig. 15, however, one might consider a more similar to b than ...
The algorithm considers both local and global similarities between sessions and incorporates three distance metrics in the computation of the distance between two sessions. We describe the three metrics and discuss the rational for combining them. The algorithm is evaluated on two datasets. One is a...
We present a new method for evaluating the relative distance between any two countries, among several, using individual data. We form clusters of respondents and we calculate the proportions of each country's respondents who belong to the various clusters. Assuming that respondents in the same clus...
Basic Examples(2) The correlation distance between two vectors: In[1]:= Out[1]= Correlation distance between numeric vectors: In[1]:= Out[1]= Scope(2) Applications(1) Properties & Relations(3) See Also CosineDistance Tech Notes Partitioning Data into Clusters Related GuidesDistance...
Then, by adopting the DTW (dynamic time warping) algorithm, distance between two sub-trajectories of any lengths can be calculated. Finally, the OPTICS(ordering points to identify the clustering structure) algorithm is applied to find clusters of sub-trajectories. Experimental results show that the...
The primary goal is to precisely compute the GBLD distance between these two lineage trees, adhering rigorously to established scientific standards. Subsequently, our focus smoothly transitions towards the systematic construction of clusters, incorporating multiple trees concurrently. This is executed with ...
Mahalanobis distance: (a) object B is closer to centroid C of cluster G1 then object A; (b) the distance between clusters G1 and G2 is smaller than between G3 and G4. In the same way, in Fig. 30.4b, clusters G1 and G2 are closer together than G3 and G4 although the ...