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  2. Predictive Model Markup Language - Wikipedia

    en.wikipedia.org/wiki/Predictive_Model_Markup...

    It contains specific information about each field, such as: Name (attribute name): must refer to a field in the data dictionary; Usage type (attribute usageType): defines the way a field is to be used in the model. Typical values are: active, predicted, and supplementary. Predicted fields are those whose values are predicted by the model.

  3. Model–view–viewmodel - Wikipedia

    en.wikipedia.org/wiki/Model–view–viewmodel

    The view model is an abstraction of the view exposing public properties and commands. Instead of the controller of the MVC pattern, or the presenter of the MVP pattern, MVVM has a binder, which automates communication between the view and its bound properties in the view model. The view model has been described as a state of the data in the ...

  4. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:

  5. Structure chart - Wikipedia

    en.wikipedia.org/wiki/Structure_Chart

    A structure chart (SC) in software engineering and organizational theory is a chart which shows the smallest of a system to its lowest manageable levels. [2] They are used in structured programming to arrange program modules into a tree. Each module is represented by a box, which contains the module's name.

  6. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    If a multilayer perceptron has a linear activation function in all neurons, that is, a linear function that maps the weighted inputs to the output of each neuron, then linear algebra shows that any number of layers can be reduced to a two-layer input-output model.

  7. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    A successive convolutional layer can then learn to assemble a precise output based on this information. [1] One important modification in U-Net is that there are a large number of feature channels in the upsampling part, which allow the network to propagate context information to higher resolution layers.

  8. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".

  9. Adaptive neuro fuzzy inference system - Wikipedia

    en.wikipedia.org/wiki/Adaptive_neuro_fuzzy...

    It is possible to identify two parts in the network structure, namely premise and consequence parts. In more details, the architecture is composed by five layers. The first layer takes the input values and determines the membership functions belonging to them. It is commonly called fuzzification layer.