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

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

    Features extracted aim at studying gesture phase segmentation. 9900 Text Classification, clustering 2014 [169] [170] R. Madeo et a Vicon Physical Action Data Set Dataset 10 normal and 10 aggressive physical actions that measure the human activity tracked by a 3D tracker. Many parameters recorded by 3D tracker. 3000 Text Classification 2011 [171 ...

  3. Feature (machine learning) - Wikipedia

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

    The initial set of raw features can be redundant and large enough that estimation and optimization is made difficult or ineffective. Therefore, a preliminary step in many applications of machine learning and pattern recognition consists of selecting a subset of features, or constructing a new and reduced set of features to facilitate learning ...

  4. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Diagram of the feature learning paradigm in ML for application to downstream tasks, which can be applied to either raw data such as images or text, or to an initial set of features of the data. Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare ...

  5. Glossary of artificial intelligence - Wikipedia

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

    data set. Also dataset. A collection of data. Most commonly a data set corresponds to the contents of a single database table, or a single statistical data matrix, where every column of the table represents a particular variable, and each row corresponds to a given member of the data set in question. The data set lists values for each of the ...

  6. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Even relatively insignificant features may contribute to a model. Feature selection can reduce the number of features to prevent a model from becoming too specific to the training data set (overfitting). [12] Feature explosion occurs when the number of identified features is too large for effective model estimation or optimization.

  7. Tag (metadata) - Wikipedia

    en.wikipedia.org/wiki/Tag_(metadata)

    A tag cloud with terms related to Web 2.0. In information systems, a tag is a keyword or term assigned to a piece of information (such as an Internet bookmark, multimedia, database record, or computer file). This kind of metadata helps describe an item and allows it to be found again by browsing or searching. [1]

  8. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  9. Web data integration - Wikipedia

    en.wikipedia.org/wiki/Web_data_integration

    Web data integration (WDI) is the process of aggregating and managing data from different websites into a single, homogeneous workflow. This process includes data access, transformation, mapping, quality assurance and fusion of data. Data that is sourced and structured from websites is referred to as "web data".