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  2. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    getML community is an open source tool for automated feature engineering on time series and relational data. [23] [24] It is implemented in C/C++ with a Python interface. [24] It has been shown to be at least 60 times faster than tsflex, tsfresh, tsfel, featuretools or kats. [24] tsfresh is a Python library for feature extraction on time series ...

  3. Feature (computer vision) - Wikipedia

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

    When feature extraction is done without local decision making, the result is often referred to as a feature image. Consequently, a feature image can be seen as an image in the sense that it is a function of the same spatial (or temporal) variables as the original image, but where the pixel values hold information about image features instead of ...

  4. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a ...

  5. Feature (machine learning) - Wikipedia

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

    In feature engineering, two types of features are commonly used: numerical and categorical. 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]

  6. Feature selection - Wikipedia

    en.wikipedia.org/wiki/Feature_selection

    Filter feature selection is a specific case of a more general paradigm called structure learning.Feature selection finds the relevant feature set for a specific target variable whereas structure learning finds the relationships between all the variables, usually by expressing these relationships as a graph.

  7. Pattern recognition - Wikipedia

    en.wikipedia.org/wiki/Pattern_recognition

    Techniques to transform the raw feature vectors (feature extraction) are sometimes used prior to application of the pattern-matching algorithm. Feature extraction algorithms attempt to reduce a large-dimensionality feature vector into a smaller-dimensionality vector that is easier to work with and encodes less redundancy, using mathematical ...

  8. The husband-wife legal team working on two of today’s ... - AOL

    www.aol.com/news/husband-wife-legal-team-working...

    The rapper Sean “Diddy” Combs and the suspected health care CEO assassin Luigi Mangione have decided on a similar defense strategy: Hire an Agnifilo.

  9. Signal processing - Wikipedia

    en.wikipedia.org/wiki/Signal_processing

    Signal processing is an electrical engineering subfield that focuses on analyzing, ... Feature extraction, such as image understanding and speech recognition.