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The description of similarities and differences found between the two things is also called a comparison. Comparison can take many distinct forms, varying by field: To compare is to bring two or more things together (physically or in contemplation) and to examine them systematically, identifying similarities and differences among them.
The Computer Language Benchmarks Game site warns against over-generalizing from benchmark data, but contains a large number of micro-benchmarks of reader-contributed code snippets, with an interface that generates various charts and tables comparing specific programming languages and types of tests.
In linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would mean a total overlap between vocabularies, whereas 0 means there are no common words. There are different ways to define the lexical similarity and the results vary accordingly.
License and pricing policies also vary among different systems. The tables below use the following terms: BSD BSD licenses are a family of permissive free software licenses, imposing minimal restrictions on the use and distribution of covered software. bundled The fee is included in the price of the hardware bundled initially
Other variations include the "similarity coefficient" or "index", such as Dice similarity coefficient (DSC). Common alternate spellings for Sørensen are Sorenson , Soerenson and Sörenson , and all three can also be seen with the –sen ending (the Danish letter ø is phonetically equivalent to the German/Swedish ö, which can be written as oe ...
Similarity measures play a crucial role in many clustering techniques, as they are used to determine how closely related two data points are and whether they should be grouped together in the same cluster. A similarity measure can take many different forms depending on the type of data being clustered and the specific problem being solved.
The SMC is very similar to the more popular Jaccard index. The main difference is that the SMC has the term in its numerator and denominator, whereas the Jaccard index does not. Thus, the SMC counts both mutual presences (when an attribute is present in both sets) and mutual absence (when an attribute is absent in both sets) as matches and ...
When used for binary attributes, the Jaccard index is very similar to the simple matching coefficient. The main difference is that the SMC has the term in its numerator and denominator, whereas the Jaccard index does not. Thus, the SMC counts both mutual presences (when an attribute is present in both sets) and mutual absence (when an attribute ...