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  2. 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]

  3. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    In computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant . [ 1 ]

  4. Respirator fit test - Wikipedia

    en.wikipedia.org/wiki/Respirator_fit_test

    However the newer OSHA Fast Fit Protocols for CNC methods, and introduction of newer instruments, have made all quantitative fit test devices equivalent in price and time required for testing. The CNP method has at present about 15% of the fit test market in industry. [25] The Current CNC instruments are the PortaCount 8040 and the AccuFIT 9000.

  5. Learning curve (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Learning_curve_(machine...

    In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and usually a validation set) changes with the number of training iterations (epochs) or the amount of training data. [1]

  6. Similarity learning - Wikipedia

    en.wikipedia.org/wiki/Similarity_learning

    Similarity learning is closely related to distance metric learning. Metric learning is the task of learning a distance function over objects. A metric or distance function has to obey four axioms: non-negativity, identity of indiscernibles, symmetry and subadditivity (or the triangle inequality). In practice, metric learning algorithms ignore ...

  7. Independent component analysis - Wikipedia

    en.wikipedia.org/wiki/Independent_component_analysis

    Maximum likelihood estimation (MLE) is a standard statistical tool for finding parameter values (e.g. the unmixing matrix ) that provide the best fit of some data (e.g., the extracted signals ) to a given a model (e.g., the assumed joint probability density function (pdf) of source signals).

  8. Computational learning theory - Wikipedia

    en.wikipedia.org/wiki/Computational_learning_theory

    Theoretical results in machine learning mainly deal with a type of inductive learning called supervised learning. In supervised learning, an algorithm is given samples that are labeled in some useful way. For example, the samples might be descriptions of mushrooms, and the labels could be whether or not the mushrooms are edible.

  9. Fit testing - Wikipedia

    en.wikipedia.org/wiki/Fit_testing

    Download as PDF; Printable version; In other projects ... move to sidebar hide. Fit testing may refer to: Fecal immunochemical testing; Hearing protection fit-testing ...