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Ishikawa diagrams (also called fishbone diagrams, [ 1] herringbone diagrams, cause-and-effect diagrams) are causal diagrams created by Kaoru Ishikawa that show the potential causes of a specific event. [ 2] Common uses of the Ishikawa diagram are product design and quality defect prevention to identify potential factors causing an overall effect.
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 ...
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 ...
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 and integrate the results ...
The Dreyfus model of skill acquisition is a model of how learners acquire skills through formal instruction and practicing, used in the fields of education and operations research. Brothers Stuart and Hubert Dreyfus proposed the model in 1980 in an 18-page report on their research at the University of California, Berkeley, Operations Research ...
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]
Bloom's taxonomy is a set of three hierarchical models used for classification of educational learning objectives into levels of complexity and specificity. The three lists cover the learning objectives in cognitive, affective and psychomotor domains. The cognitive domain list has been the primary focus of most traditional education and is ...
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 ...