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  2. Data reduction - Wikipedia

    en.wikipedia.org/wiki/Data_reduction

    Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications

  3. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Dimensionality reduction; ... Data mining is the process of extracting and ... and data snooping refer to the use of data mining methods to sample parts of a larger ...

  4. Dimensionality reduction - Wikipedia

    en.wikipedia.org/wiki/Dimensionality_reduction

    Methods are commonly divided into linear and nonlinear approaches. [1] Linear approaches can be further divided into feature selection and feature extraction. [2] Dimensionality reduction can be used for noise reduction, data visualization, cluster analysis, or as an intermediate step to facilitate other analyses.

  5. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  6. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    Many methods have been invented to extract a low-dimensional structure from the data set, such as principal component analysis and multidimensional scaling. [27] However, it is important to note that the problem itself is ill-posed, since many different topological features can be found in the same data set.

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    In information theory, data compression, source coding, [1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in ...

  8. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    One data mining method that is used to perform this task is known as multifactor dimensionality reduction. [15] In the area of electrical power engineering, data mining methods have been widely used for condition monitoring of high voltage electrical equipment.

  9. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...