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Model Review: Provide students with sample assignments of varying quality for analysis. Criteria Listing: Collaboratively list criteria for the scoring rubric, incorporating student feedback. Quality Gradations: Define hierarchical categories describing levels of quality or development.
While analytic grading involves criterion-by-criterion judgments, holistic grading appraises student works as integrated entities. In holistic grading, the learner's performance is approached as one and cannot be reduced or divided into several component performances. [ 17 ]
Model selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. [1] In the context of machine learning and more generally statistical analysis , this may be the selection of a statistical model from a set of candidate models, given data.
AHP stands for analytic hierarchy process – a multi-criteria decision-making (MCDM) method. In AHP, values like price, weight, or area, or even subjective opinions such as feelings, preferences, or satisfaction, can be translated into measurable numeric relations.
Model the problem as a hierarchy containing the decision goal, the alternatives for reaching it, and the criteria for evaluating the alternatives. Establish priorities among the elements of the hierarchy by making a series of judgments based on pairwise comparisons of the elements.
The categories are: Damage – how bad would an attack be?; Reproducibility – how easy is it to reproduce the attack?; Exploitability – how much work is it to launch the attack?
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The applications of Promethee and Gaia to complex multi-criteria decision scenarios have numbered in the thousands, and have produced extensive results in problems involving planning, resource allocation, priority setting, and selection among alternatives. Other areas have included forecasting, talent selection, and tender analysis.