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In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.
However, the language also offers various alternatives to complex forms of memory management. Reference counting functionality is provided by the Rc and Arc types, which are non-atomic and atomic respectively. For example, the type Rc<T> provides shared ownership of a value of type T, allocated on the heap for multiple references to its data. [22]
In computing, the count–min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data.It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space, at the expense of overcounting some events due to collisions.
A counting Bloom filter is a probabilistic data structure that is used to test whether the number of occurrences of a given element in a sequence exceeds a given threshold. As a generalized form of the Bloom filter, false positive matches are possible, but false negatives are not – in other words, a query returns either "possibly bigger or equal than the threshold" or "definitely smaller ...
Cell counting is any of various methods for the counting or similar quantification of cells in the life sciences, including medical diagnosis and treatment. It is an important subset of cytometry , with applications in research and clinical practice.
The counting measure is a special case of a more general construction. With the notation as above, any function : [,) defines a measure on (,) via ():= (), where the possibly uncountable sum of real numbers is defined to be the supremum of the sums over all finite subsets, that is, := , | | < {}.
When creating a data-set of terms that appear in a corpus of documents, the document-term matrix contains rows corresponding to the documents and columns corresponding to the terms. Each ij cell, then, is the number of times word j occurs in document i. As such, each row is a vector of term counts that represents the content of the document ...
Because CellProfiler is a free, open-source project, anyone can develop their own image processing algorithms as a new module for CellProfiler and contribute it to the project. [18] The CellProfiler website contains a forum for discussion where new users can have their questions answered, usually by the creators of the project.