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  2. Explainable artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Explainable_artificial...

    It is usually done using permutation importance, which measures the performance decrease when it the feature value randomly shuffled across all samples. LIME approximates locally a model's outputs with a simpler, interpretable model. [41] Multitask learning provides a large number of outputs in addition to the target classification. These other ...

  3. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  4. Glossary of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_artificial...

    The data set lists values for each of the variables, such as height and weight of an object, for each member of the data set. Each value is known as a datum. The data set may comprise data for one or more members, corresponding to the number of rows. data warehouse (DW or DWH) Also enterprise data warehouse (EDW).

  5. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    Numerical features are continuous values that can be measured on a scale. Examples of numerical features include age, height, weight, and income. Numerical features can be used in machine learning algorithms directly. [citation needed] Categorical features are discrete values that can be grouped into categories. Examples of categorical features ...

  6. Quantification (machine learning) - Wikipedia

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

    In machine learning and data mining, quantification (variously called learning to quantify, or supervised prevalence estimation, or class prior estimation) is the task of using supervised learning in order to train models (quantifiers) that estimate the relative frequencies (also known as prevalence values) of the classes of interest in a sample of unlabelled data items.

  7. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

  8. Huge number of AI-generated songs on streaming services ... - AOL

    www.aol.com/streaming-deezer-launches-ai-music...

    Huge number of AI-generated songs on streaming services exposed by Deezer. Andrew Griffin. January 25, 2025 at 10:07 AM ... and has the option to add more if there are enough data examples available.

  9. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    ML involves the study and construction of algorithms that can learn from and make predictions on data. [3] These algorithms operate by building a model from a training set of example observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.