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This is also called unity-based normalization. This can be generalized to restrict the range of values in the dataset between any arbitrary points a {\displaystyle a} and b {\displaystyle b} , using for example X ′ = a + ( X − X min ) ( b − a ) X max − X min {\displaystyle X'=a+{\frac {\left(X-X_{\min }\right)\left(b-a\right)}{X_{\max ...
In computer science, canonicalization (sometimes standardization or normalization) is a process for converting data that has more than one possible representation into a "standard", "normal", or canonical form.
Normalization is defined as the division of each element in the kernel by the sum of all kernel elements, so that the sum of the elements of a normalized kernel is unity. This will ensure the average pixel in the modified image is as bright as the average pixel in the original image.
Unicode equivalence is the specification by the Unicode character encoding standard that some sequences of code points represent essentially the same character. This feature was introduced in the standard to allow compatibility with pre-existing standard character sets, which often included similar or identical characters.
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 message "Script error" only occurs when the test data triggers an invalid section of Lua code, so an untested module could contain many hidden bugs, ...
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Least absolute deviations (LAD), also known as least absolute errors (LAE), least absolute residuals (LAR), or least absolute values (LAV), is a statistical optimality criterion and a statistical optimization technique based on minimizing the sum of absolute deviations (also sum of absolute residuals or sum of absolute errors) or the L 1 norm of such values.