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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. 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.

  4. 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).

  5. 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..

  6. Normalization (machine learning) - Wikipedia

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

    Query-Key normalization (QKNorm) [32] normalizes query and key vectors to have unit L2 norm. In nGPT, many vectors are normalized to have unit L2 norm: [33] hidden state vectors, input and output embedding vectors, weight matrix columns, and query and key vectors.

  7. 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).

  8. Nondimensionalization - Wikipedia

    en.wikipedia.org/wiki/Nondimensionalization

    Nondimensionalization determines in a systematic manner the characteristic units of a system to use, without relying heavily on prior knowledge of the system's intrinsic properties (one should not confuse characteristic units of a system with natural units of nature). In fact, nondimensionalization can suggest the parameters which should be ...

  9. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Simpler queries – star-schema join-logic is generally simpler than the join logic required to retrieve data from a highly normalized transactional schema. Simplified business reporting logic – when compared to highly normalized schemas, the star schema simplifies common business reporting logic, such as period-over-period and as-of reporting.