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Classification and clustering are examples of the more general problem of pattern recognition, which is the assignment of some sort of output value to a given input value. Other examples are regression, which assigns a real-valued output to each input; sequence labeling, which assigns a class to each member of a sequence of values (for example ...
Hydrostatics, also known as fluid statics, is the study of fluids at rest (i.e. in static equilibrium). The characteristic of any fluid at rest is that the force exerted on any particle of the fluid is the same at all points at the same depth (or altitude) within the fluid.
A representation of the relation among complexity classes. This is a list of complexity classes in computational complexity theory. For other computational and complexity subjects, see list of computability and complexity topics. Many of these classes have a 'co' partner which consists of the complements of all languages in the original class ...
In statistics, completeness is a property of a statistic computed on a sample dataset in relation to a parametric model of the dataset. It is opposed to the concept of an ancillary statistic . While an ancillary statistic contains no information about the model parameters, a complete statistic contains only information about the parameters, and ...
For example, the sample mean is an unbiased estimator of the population mean. This means that the expected value of the sample mean equals the true population mean. [1] A descriptive statistic is used to summarize the sample data. A test statistic is used in statistical hypothesis testing. A single statistic can be used for multiple purposes ...
In business, "statistics" is a widely used management-and decision support tool. It is particularly applied in financial management, marketing management, and production, services and operations management. [69] [70] Statistics is also heavily used in management accounting and auditing.
NC i is the class of decision problems decidable by uniform boolean circuits with a polynomial number of gates of at most two inputs and depth O((log n) i), or the class of decision problems solvable in time O((log n) i) on a parallel computer with a polynomial number of processors. Clearly, we have
The W hierarchy is a collection of computational complexity classes. A parameterized problem is in the class W[i], if every instance (,) can be transformed (in fpt-time) to a combinatorial circuit that has weft at most i, such that (,) if and only if there is a satisfying assignment to the inputs that assigns 1 to exactly k inputs.