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  2. Normalization (statistics) - Wikipedia

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

    In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...

  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. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

  5. Normalization (machine learning) - Wikipedia

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

    Instance normalization (InstanceNorm), or contrast normalization, is a technique first developed for neural style transfer, and is also only used for CNNs. [26] It can be understood as the LayerNorm for CNN applied once per channel, or equivalently, as group normalization where each group consists of a single channel:

  6. Normal score - Wikipedia

    en.wikipedia.org/wiki/Normal_score

    The term normal score is used with two different meanings in statistics. One of them relates to creating a single value which can be treated as if it had arisen from a standard normal distribution (zero mean, unit variance). The second one relates to assigning alternative values to data points within a dataset, with the broad intention of ...

  7. Quantile normalization - Wikipedia

    en.wikipedia.org/wiki/Quantile_normalization

    In statistics, quantile normalization is a technique for making two distributions identical in statistical properties. To quantile-normalize a test distribution to a reference distribution of the same length, sort the test distribution and sort the reference distribution.

  8. Normalization - Wikipedia

    en.wikipedia.org/wiki/Normalization

    Normalization model, used in visual neuroscience; Normalization in quantum mechanics, see Wave function § Normalization condition and normalized solution; Normalization (sociology) or social normalization, the process through which ideas and behaviors that may fall outside of social norms come to be regarded as "normal"

  9. Standardized coefficient - Wikipedia

    en.wikipedia.org/wiki/Standardized_coefficient

    Critics voice concerns that such a standardization can be very misleading. [2] [4] Due to the re-scaling based on sample standard deviations, any effect apparent in the standardized coefficient may be due to confounding with the particularities (especially: variability) of the involved data sample(s).