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  2. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    In supervised learning, the training data is labeled with the expected answers, while in unsupervised learning, the model identifies patterns or structures in unlabeled data. Supervised learning ( SL ) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as a ...

  3. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...

  4. List of artificial intelligence projects - Wikipedia

    en.wikipedia.org/wiki/List_of_artificial...

    Blue Brain Project, an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level. [1] Google Brain, a deep learning project part of Google X attempting to have intelligence similar or equal to human-level. [2] Human Brain Project, ten-year scientific research project, based on exascale ...

  5. Random forest - Wikipedia

    en.wikipedia.org/wiki/Random_forest

    Decision trees are a popular method for various machine learning tasks. Tree learning is almost "an off-the-shelf procedure for data mining", say Hastie et al., "because it is invariant under scaling and various other transformations of feature values, is robust to inclusion of irrelevant features, and produces inspectable models.

  6. 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]

  7. Structured prediction - Wikipedia

    en.wikipedia.org/wiki/Structured_prediction

    Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured objects, rather than discrete or real values. [ 1 ]

  8. Imitation learning - Wikipedia

    en.wikipedia.org/wiki/Imitation_learning

    Imitation learning is a paradigm in reinforcement learning, where an agent learns to perform a task by supervised learning from expert demonstrations. It is also called learning from demonstration and apprenticeship learning .

  9. Category:Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Category:Supervised_learning

    In other projects Wikidata item; Appearance. move to sidebar hide. Help ... Pages in category "Supervised learning" The following 6 pages are in this category, out of ...