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

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

    A test data set is a data set that is independent of the training data set, but that follows the same probability distribution as the training data set. If a model fit to the training data set also fits the test data set well, minimal overfitting has taken place (see figure below). A better fitting of the training data set as opposed to the ...

  3. DBSCAN - Wikipedia

    en.wikipedia.org/wiki/DBSCAN

    The basic idea has been extended to hierarchical clustering by the OPTICS algorithm. DBSCAN is also used as part of subspace clustering algorithms like PreDeCon and SUBCLU . HDBSCAN* [ 6 ] [ 7 ] is a hierarchical version of DBSCAN which is also faster than OPTICS, from which a flat partition consisting of the most prominent clusters can be ...

  4. Analytic hierarchy process - Wikipedia

    en.wikipedia.org/wiki/Analytic_hierarchy_process

    Human organizations are often structured as hierarchies, where the hierarchical system is used for assigning responsibilities, exercising leadership, and facilitating communication. Familiar hierarchies of "things" include a desktop computer's tower unit at the "top", with its subordinate monitor, keyboard, and mouse "below."

  5. Multilevel model - Wikipedia

    en.wikipedia.org/wiki/Multilevel_model

    However, the test can only be used when models are nested (meaning that a more complex model includes all of the effects of a simpler model). When testing non-nested models, comparisons between models can be made using the Akaike information criterion (AIC) or the Bayesian information criterion (BIC), among others. [1] [2] [5] See further Model ...

  6. Bayesian hierarchical modeling - Wikipedia

    en.wikipedia.org/wiki/Bayesian_hierarchical_modeling

    Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the parameters of the posterior distribution using the Bayesian method. [1] The sub-models combine to form the hierarchical model, and Bayes' theorem is used to integrate them with the observed data and account for all the ...

  7. Predictive coding - Wikipedia

    en.wikipedia.org/wiki/Predictive_coding

    This makes predictive coding similar to some other models of hierarchical learning, such as Helmholtz machines and Deep belief networks, which however employ different learning algorithms. Thus, the dual use of prediction errors for both inference and learning is one of the defining features of predictive coding. [6]

  8. These are the fastest-growing job titles, according to ...

    www.aol.com/fastest-growing-job-titles-according...

    Hospitality and travel-related roles were among some of the fastest-growing jobs, according to LinkedIn's analysis of user data. (Thomas Barwick/Digital Vision/Getty Images)

  9. Tree testing - Wikipedia

    en.wikipedia.org/wiki/Tree_testing

    Tree testing is a usability technique for evaluating the findability of topics in a website. [1] It is also known as reverse card sorting or card-based classification. [2] A large website is typically organized into a hierarchy (a "tree") of topics and subtopics. [3] [4] Tree testing provides a way to measure how well users can find items in ...