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  2. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    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 ...

  3. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).

  4. Quantile normalization - Wikipedia

    en.wikipedia.org/wiki/Quantile_normalization

    To quantile normalize two or more distributions to each other, without a reference distribution, sort as before, then set to the average (usually, arithmetic mean) of the distributions. So the highest value in all cases becomes the mean of the highest values, the second highest value becomes the mean of the second highest values, and so on.

  5. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .

  6. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    Data normalization (or feature scaling) includes methods that rescale input data so that the features have the same range, mean, variance, or other statistical properties. For instance, a popular choice of feature scaling method is min-max normalization , where each feature is transformed to have the same range (typically [ 0 , 1 ...

  7. Orders of magnitude (data) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude_(data)

    The order of magnitude of data may be specified in strictly standards-conformant units of information and multiples of the bit and byte with decimal scaling, or using historically common usages of a few multiplier prefixes in a binary interpretation which has been common in computing until new binary prefixes were defined in the 1990s..

  8. Normalized frequency (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Normalized_frequency...

    Therefore, the normalized frequency unit is important when converting normalized results into physical units. Example of plotting samples of a frequency distribution in the unit "bins", which are integer values. A scale factor of 0.7812 converts a bin number into the corresponding physical unit (hertz).

  9. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In fluid dynamics, normalized root mean square deviation (NRMSD), coefficient of variation (CV), and percent RMS are used to quantify the uniformity of flow behavior such as velocity profile, temperature distribution, or gas species concentration. The value is compared to industry standards to optimize the design of flow and thermal equipment ...