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The Duncan Segregation Index is a measure of occupational segregation based on gender that measures whether there is a larger than expected presence of one gender over another in a given occupation or labor force by identifying the percentage of employed women (or men) who would have to change occupations for the occupational distribution of men and women to be equal.
The index of dissimilarity is a demographic measure of the evenness with which two groups are distributed across component geographic areas that make up a larger area. A group is evenly distributed when each geographic unit has the same percentage of group members as the total population.
In statistics, Gower's distance between two mixed-type objects is a similarity measure that can handle different types of data within the same dataset and is particularly useful in cluster analysis or other multivariate statistical techniques. Data can be binary, ordinal, or continuous variables.
As such, for two objects and having descriptors, the similarity is defined as: = = =, where the are non-negative weights and is the similarity between the two objects regarding their -th variable. In spectral clustering , a similarity, or affinity, measure is used to transform data to overcome difficulties related to lack of convexity in the ...
PETSc includes a large suite of parallel linear and nonlinear equation solvers that are easily used in application codes written in C, C++, Fortran and now Python. PETSc provides many of the mechanisms needed within parallel application code, such as simple parallel matrix and vector assembly routines that allow the overlap of communication and ...
For example, consider a supermarket with 1000 products and two customers. The basket of the first customer contains salt and pepper and the basket of the second contains salt and sugar. In this scenario, the similarity between the two baskets as measured by the Jaccard index would be 1/3, but the similarity becomes 0.998 using the SMC.
For example, given nodes a,b,c such that a,b and a,c are similar while b,c are dissimilar, a perfect clustering is not possible. In such cases, the task is to find a clustering that maximizes the number of agreements (number of + edges inside clusters plus the number of − edges between clusters) or minimizes the number of disagreements (the ...
Ind-objects in C form a category ind-C.. Two ind-objects : and : determine a functor I op x J Sets,. namely the functor ((), ()). The set of morphisms between F and G in Ind(C) is defined to be the colimit of this functor in the second variable, followed by the limit in the first variable: