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  2. Second normal form - Wikipedia

    en.wikipedia.org/wiki/Second_normal_form

    Second normal form (2NF), in database normalization, is a normal form. A relation is in the second normal form if it fulfills the following two requirements: A relation is in the second normal form if it fulfills the following two requirements:

  3. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Codd introduced the concept of normalization and what is now known as the first normal form (1NF) in 1970. [4] Codd went on to define the second normal form (2NF) and third normal form (3NF) in 1971, [5] and Codd and Raymond F. Boyce defined the Boyce–Codd normal form (BCNF) in 1974. [6]

  4. Chain rule (probability) - Wikipedia

    en.wikipedia.org/wiki/Chain_rule_(probability)

    This rule allows one to express a joint probability in terms of only conditional probabilities. [4] The rule is notably used in the context of discrete stochastic processes and in applications, e.g. the study of Bayesian networks, which describe a probability distribution in terms of conditional probabilities.

  5. First normal form - Wikipedia

    en.wikipedia.org/wiki/First_normal_form

    First normal form (1NF) is a property of a relation in a relational database. A relation is in first normal form if and only if no attribute domain has relations as elements. [ 1 ] Or more informally, that no table column can have tables as values.

  6. Talk:Database normalization - Wikipedia

    en.wikipedia.org/wiki/Talk:Database_normalization

    Even if you provide a mathematical definition of 1NF, being in 1NF will be independent from being in 2NF. The quote from the article is wrong if 1NF is included. 2NF and higher are defined mathematically, and these definitions are such that for each i > j > 1, every database in iNF is also in jNF. Hence, for all NFs above 1, the quote is correct.

  7. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    [3] [4] Presently, the two types are highly correlated and complementary and both have a wide variety of applications in, e.g., non-linear optimization, sensitivity analysis, robotics, machine learning, computer graphics, and computer vision. [5] [10] [3] [4] [11] [12] Automatic differentiation is particularly important in the field of machine ...

  8. Unit propagation - Wikipedia

    en.wikipedia.org/wiki/Unit_propagation

    Resolution calculi that include subsumption can model rule one by subsumption and rule two by a unit resolution step, followed by subsumption. Unit propagation, applied repeatedly as new unit clauses are generated, is a complete satisfiability algorithm for sets of propositional Horn clauses ; it also generates a minimal model for the set if ...

  9. Third normal form - Wikipedia

    en.wikipedia.org/wiki/Third_normal_form

    every element of Y \ X, the set difference between Y and X, is a prime attribute (i.e., each attribute in Y \ X is contained in some candidate key). To rephrase Zaniolo's definition more simply, the relation is in 3NF if and only if for every non-trivial functional dependency X → Y, X is a superkey or Y \ X consists of prime attributes.