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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 (machine learning) - Wikipedia

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

    Extracting or selecting features is a combination of art and science; developing systems to do so is known as feature engineering. It requires the experimentation of multiple possibilities and the combination of automated techniques with the intuition and knowledge of the domain expert .

  5. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that ML tasks such as classification often require input that is mathematically and computationally convenient to process. However, real-world data, such as image, video, and ...

  6. Feature selection - Wikipedia

    en.wikipedia.org/wiki/Feature_selection

    In machine learning, feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret, [1] shorter training times, [2] to avoid the curse of dimensionality, [3]

  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. Signal processing - Wikipedia

    en.wikipedia.org/wiki/Signal_processing

    Process control – a variety of signals are used, including the industry standard 4-20 mA current loop; Seismology; Feature extraction, such as image understanding and speech recognition. Quality improvement, such as noise reduction, image enhancement, and echo cancellation.

  9. Process science - Wikipedia

    en.wikipedia.org/wiki/Process_science

    Process science is the method of describing change from an inquiry-oriented process perspective. [1] [2] [3] Process science includes algorithms, heuristics, and sequences found in psychology, linguistics, anthropology, politics, and economics. [4] In sociology, processes are temporal. [5] In computer science, a process is the collective input ...