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  2. 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 ...

  3. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Without normalization, the clusters were arranged along the x-axis, since it is the axis with most of variation. After normalization, the clusters are recovered as expected. In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature ...

  4. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database 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 .

  5. Normalization (statistics) - Wikipedia

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

    In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment.

  6. Cardinality (data modeling) - Wikipedia

    en.wikipedia.org/wiki/Cardinality_(data_modeling)

    Codd's steps for organizing database tables and their keys is called database normalization, which avoids certain hidden database design errors (delete anomalies or update anomalies). In real life the process of database normalization ends up breaking tables into a larger number of smaller tables. [3]

  7. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    Normalization splits up data to avoid redundancy (duplication) by moving commonly repeating groups of data into new tables. Normalization therefore tends to increase the number of tables that need to be joined in order to perform a given query, but reduces the space required to hold the data and the number of places where it needs to be updated if the data changes.

  8. Third normal form - Wikipedia

    en.wikipedia.org/wiki/Third_normal_form

    The third normal form (3NF) is a normal form used in database normalization. 3NF was originally defined by E. F. Codd in 1971. [2] Codd's definition states that a table is in 3NF if and only if both of the following conditions hold: The relation R (table) is in second normal form (2NF).

  9. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Relational models require a strict schema and data normalization which separates data into many tables and removes any duplicate data within the database. Data is normalized in order to preserve data consistency and support ACID transactions. However this imposes limitations on how relationships can be queried.