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  2. Decision tree - Wikipedia

    en.wikipedia.org/wiki/Decision_tree

    A decision tree is a flowchart -like structure in which each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent ...

  3. Influence diagram - Wikipedia

    en.wikipedia.org/wiki/Influence_diagram

    An influence diagram (ID) (also called a relevance diagram, decision diagram or a decision network) is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network, in which not only probabilistic inference problems but also decision making problems (following the maximum expected ...

  4. Binary decision diagram - Wikipedia

    en.wikipedia.org/wiki/Binary_decision_diagram

    Binary decision diagram. In computer science, a binary decision diagram (BDD) or branching program is a data structure that is used to represent a Boolean function. On a more abstract level, BDDs can be considered as a compressed representation of sets or relations. Unlike other compressed representations, operations are performed directly on ...

  5. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    v. t. e. Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called ...

  6. ID3 algorithm - Wikipedia

    en.wikipedia.org/wiki/ID3_algorithm

    Values of attributes are represented by branches. In decision tree learning, ID3 (Iterative Dichotomiser 3) is an algorithm invented by Ross Quinlan [1] used to generate a decision tree from a dataset. ID3 is the precursor to the C4.5 algorithm, and is typically used in the machine learning and natural language processing domains.

  7. Tree diagram (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Tree_diagram_(probability...

    v. t. e. In probability theory, a tree diagram may be used to represent a probability space. A tree diagram may represent a series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck, without replacing the cards). [1] Each node on the diagram represents an event and is associated ...

  8. Argument map - Wikipedia

    en.wikipedia.org/wiki/Argument_map

    v. t. e. An argument map or argument diagram is a visual representation of the structure of an argument. An argument map typically includes all the key components of the argument, traditionally called the conclusion and the premises, also called contention and reasons. [1] Argument maps can also show co-premises, objections, counterarguments ...

  9. Decision tree model - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_model

    Decision Tree Model. In computational complexity the decision tree model is the model of computation in which an algorithm is considered to be basically a decision tree, i.e., a sequence of queries or tests that are done adaptively, so the outcome of previous tests can influence the tests performed next. Typically, these tests have a small ...