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  2. Active learning (machine learning) - Wikipedia

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

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

  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. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  5. Syncope (medicine) - Wikipedia

    en.wikipedia.org/wiki/Syncope_(medicine)

    Syncope ((syncope ⓘ), commonly known as fainting or passing out, is a loss of consciousness and muscle strength characterized by a fast onset, short duration, and spontaneous recovery. [1] It is caused by a decrease in blood flow to the brain , typically from low blood pressure . [ 1 ]

  6. Computational learning theory - Wikipedia

    en.wikipedia.org/wiki/Computational_learning_theory

    Online machine learning, from the work of Nick Littlestone [citation needed]. While its primary goal is to understand learning abstractly, computational learning theory has led to the development of practical algorithms. For example, PAC theory inspired boosting, VC theory led to support vector machines, and Bayesian inference led to belief ...

  7. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]

  8. Digital phenotyping - Wikipedia

    en.wikipedia.org/wiki/Digital_phenotyping

    Digital phenotyping is a multidisciplinary field of science, [1] [2] [3] first defined in a May 2016 paper in JMIR Mental Health authored by John Torous, Mathew V Kiang, Jeanette Lorme, and Jukka-Pekka Onnela as the "moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices."

  9. Category:Machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning

    Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts. The main article for this category is Machine learning . Wikimedia Commons has media related to Machine learning .