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  2. Model selection - Wikipedia

    en.wikipedia.org/wiki/Model_selection

    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.

  3. Specification by example - Wikipedia

    en.wikipedia.org/wiki/Specification_by_example

    Highly abstract or novel new concepts can be difficult to understand without concrete examples. [citation needed] Specification by example is intended to construct an accurate understanding, and significantly reduces feedback loops in software development, leading to less rework, higher product quality, faster turnaround time for software changes and better alignment of activities of various ...

  4. Optimality criterion - Wikipedia

    en.wikipedia.org/wiki/Optimality_criterion

    A model is designated as the "best" of the candidate models if it gives the best value of an objective function measuring the degree of satisfaction of the criterion used to evaluate the alternative hypotheses. The term has been used to identify the different criteria that are used to evaluate a phylogenetic tree. For example, in order to ...

  5. Situation, task, action, result - Wikipedia

    en.wikipedia.org/wiki/Situation,_task,_action...

    The situation, task, action, result (STAR) format is a technique [1] used by interviewers to gather all the relevant information about a specific capability that the job requires.

  6. Statistical model specification - Wikipedia

    en.wikipedia.org/wiki/Statistical_model...

    One approach is to start with a model in general form that relies on a theoretical understanding of the data-generating process. Then the model can be fit to the data and checked for the various sources of misspecification, in a task called statistical model validation. Theoretical understanding can then guide the modification of the model in ...

  7. 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]

  8. Research question - Wikipedia

    en.wikipedia.org/wiki/Research_question

    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.

  9. Analytic hierarchy process – car example - Wikipedia

    en.wikipedia.org/wiki/Analytic_hierarchy_process...

    The goal is green, the criteria and subcriteria are yellow, and the alternatives are pink. All the alternatives (three different models of Honda) are shown below the lowest level of each criterion. Later in the process, each alternative (each model) will be rated with respect to the criterion or subcriterion directly above it.