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In machine learning and data mining, quantification (variously called learning to quantify, or supervised prevalence estimation, or class prior estimation) is the task of using supervised learning in order to train models (quantifiers) that estimate the relative frequencies (also known as prevalence values) of the classes of interest in a sample of unlabelled data items.
For example, to measure the first stabilizer (), a parity measurement of of the first qubit, on the second, on the third, on the fourth, and on the fifth is performed. Since there are four stabilizers, 4 ancillas will be used to measure them.
An example of a source of this uncertainty would be the drag in an experiment designed to measure the acceleration of gravity near the earth's surface. The commonly used gravitational acceleration of 9.8 m/s² ignores the effects of air resistance, but the air resistance for the object could be measured and incorporated into the experiment to ...
In computing, a roundoff error, [1] also called rounding error, [2] is the difference between the result produced by a given algorithm using exact arithmetic and the result produced by the same algorithm using finite-precision, rounded arithmetic. [3]
The following example demonstrates how to describe types that can be compared to each other and use this as typing information in polymorphic functions. The Test.min function uses simple bounded quantification and does not ensure the objects are mutually comparable, in contrast with the Test.fMin function which uses F-bounded quantification.
construction destruction ABAP Objects: data variable type ref to class . create object variable «exporting parameter = argument». [1][2] [3]APL (Dyalog) : variable←⎕NEW class «parameters»
For example, in Zermelo–Fraenkel set theory, variables range over all sets. In this case, guarded quantifiers can be used to mimic a smaller range of quantification. Thus in the example above, to express For every natural number n, n·2 = n + n. in Zermelo–Fraenkel set theory, one would write For every n, if n belongs to N, then n·2 = n + n,
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