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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 ...
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 ...
Fast-and-frugal tree or matching heuristic[ 1] (in the study of decision-making) is a simple graphical structure that categorizes objects by asking one question at a time. These decision trees are used in a range of fields: psychology, artificial intelligence, and management science. Unlike other decision or classification trees, such as Leo ...
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 ...
Research. A research question is "a question that a research project sets out to answer". [ 1] Choosing a research question is an essential element of both quantitative and qualitative research. Investigation will require data collection and analysis, and the methodology for this will vary widely.
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 ...
Many of the questions and concerns come from an honest place. Nobody thinks an uneven playing field should be tolerated anywhere at the Olympics, but especially in a combat sport. You lose a foot ...
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]