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  2. Many-to-many (data model) - Wikipedia

    en.wikipedia.org/wiki/Many-to-many_(data_model)

    For example, think of A as Authors, and B as Books. An Author can write several Books, and a Book can be written by several Authors. In a relational database management system, such relationships are usually implemented by means of an associative table (also known as join table, junction table or cross-reference table), say, AB with two one-to-many relationships A → AB and B → AB.

  3. SQLAlchemy - Wikipedia

    en.wikipedia.org/wiki/SQLAlchemy

    The following example represents an n-to-1 relationship between movies and their directors. It is shown how user-defined Python classes create corresponding database tables, how instances with relationships are created from either side of the relationship, and finally how the data can be queried — illustrating automatically generated SQL ...

  4. List of object–relational mapping software - Wikipedia

    en.wikipedia.org/wiki/List_of_object–relational...

    Storm, open source (LGPL 2.1) developed at Canonical Ltd. Tryton, open source; web2py, the facilities of an ORM are handled by the DAL in web2py, open source; Odoo – Formerly known as OpenERP, It is an Open Source ERP in which ORM is included.

  5. Object–relational mapping - Wikipedia

    en.wikipedia.org/wiki/Object–relational_mapping

    Object–relational mapping (ORM, O/RM, and O/R mapping tool) in computer science is a programming technique for converting data between a relational database and the memory (usually the heap) of an object-oriented programming language.

  6. Cardinality (data modeling) - Wikipedia

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

    A one-to-many relationship between records in patient and records in appointment because patients can have many appointments and each appointment involves only one patient. [ 1 ] A one-to-one relationship is mostly used to split a table in two in order to provide information concisely and make it more understandable.

  7. Diffusion map - Wikipedia

    en.wikipedia.org/wiki/Diffusion_map

    This is a major difference with methods such as principal component analysis, where correlations between all data points are taken into account at once. Given ( X , k ) {\displaystyle (X,k)} , we can then construct a reversible discrete-time Markov chain on X {\displaystyle X} (a process known as the normalized graph Laplacian construction):

  8. Large deformation diffeomorphic metric mapping - Wikipedia

    en.wikipedia.org/wiki/Large_deformation_diffeom...

    The use of diffeomorphic methods grew quickly to dominate the field of mapping methods post Christensen's original paper, with fast and symmetric methods becoming available. [19] [34] Such methods are powerful in that they introduce notions of regularity of the solutions so that they can be differentiated and local inverses can be calculated.

  9. Fuzzy cognitive map - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_cognitive_map

    Fuzzy cognitive maps are signed fuzzy directed graphs. Spreadsheets or tables are used to map FCMs into matrices for further computation. FCM is a technique used for causal knowledge acquisition and representation, it supports causal knowledge reasoning process and belong to the neuro-fuzzy system that aim at solving decision making problems, modeling and simulate complex systems. [4]