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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 ...
A common solution has been to run the algorithm multiple times with different hash functions and combine the results from the different runs. One idea is to take the mean of the results together from each hash function, obtaining a single estimate of the cardinality. The problem with this is that averaging is very susceptible to outliers (which ...
A wide variety of measurements can be generated for each identified cell or subcellular compartment, including morphology, intensity, and texture among others. These measurements are accessible by using built-in viewing and plotting data tools, exporting in a comma-delimited spreadsheet format, [ 9 ] or importing into a MySQL or SQLite database.
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.
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.
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 connected component containing the special vertex contains the objects that can't be collected, while other connected components of the graph only contain garbage. If a reference-counting garbage collection algorithm is implemented, then each of these garbage components must contain at least one cycle; otherwise, they would have been ...
The intensity of a counting process is a measure of the rate of change of its predictable part. If a stochastic process { N ( t ) , t ≥ 0 } {\displaystyle \{N(t),t\geq 0\}} is a counting process, then it is a submartingale , and in particular its Doob-Meyer decomposition is