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  2. Root cause analysis - Wikipedia

    en.wikipedia.org/wiki/Root_cause_analysis

    Root cause analysis. In the field of science and engineering, root cause analysis ( RCA) is a method of problem solving used for identifying the root causes of faults or problems. [ 1] It is widely used in IT operations, manufacturing, telecommunications, industrial process control, accident analysis (e.g., in aviation, [ 2] rail transport, or ...

  3. Argument map - Wikipedia

    en.wikipedia.org/wiki/Argument_map

    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, rebuttals ...

  4. 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 ...

  5. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  6. Random forest - Wikipedia

    en.wikipedia.org/wiki/Random_forest

    Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of the random forest is the class selected by most trees. For regression tasks, the mean or average prediction ...

  7. Constructing skill trees - Wikipedia

    en.wikipedia.org/wiki/Constructing_skill_trees

    Constructing skill trees. Constructing skill trees (CST) is a hierarchical reinforcement learning algorithm which can build skill trees from a set of sample solution trajectories obtained from demonstration. CST uses an incremental MAP ( maximum a posteriori) change point detection algorithm to segment each demonstration trajectory into skills ...

  8. Cross-reference - Wikipedia

    en.wikipedia.org/wiki/Cross-reference

    In programming, "cross-referencing" means the listing of every file name and line number where a given named identifier occurs within the program's source tree. In a relational database management system, a table can have an xref as prefix or suffix to indicate it is a cross-reference table that joins two or more tables together via primary key.

  9. Technology tree - Wikipedia

    en.wikipedia.org/wiki/Technology_tree

    The tech tree is the representation of all possible paths of research a player can take, up to the culmination of said sequence. A player who is engaged in research activities is said to be "teching up", "going up the tech tree", or "moving up the tech tree". Analysis of a tech tree can lead players to memorize and use specific build orders .