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  2. Approximate entropy - Wikipedia

    en.wikipedia.org/wiki/Approximate_entropy

    Lower computational demand. ApEn can be designed to work for small data samples (< points) and can be applied in real time. Less effect from noise. If data is noisy, the ApEn measure can be compared to the noise level in the data to determine what quality of true information may be present in the data.

  3. 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.

  4. Maximal information coefficient - Wikipedia

    en.wikipedia.org/wiki/Maximal_information...

    The maximal information coefficient uses binning as a means to apply mutual information on continuous random variables. Binning has been used for some time as a way of applying mutual information to continuous distributions; what MIC contributes in addition is a methodology for selecting the number of bins and picking a maximum over many possible grids.

  5. Information theory - Wikipedia

    en.wikipedia.org/wiki/Information_theory

    Using a statistical description for data, information theory quantifies the number of bits needed to describe the data, which is the information entropy of the source. Data compression (source coding): There are two formulations for the compression problem: lossless data compression: the data must be reconstructed exactly;

  6. Quantities of information - Wikipedia

    en.wikipedia.org/wiki/Quantities_of_information

    This is a measure of how much information can be obtained about one random variable by observing another. The mutual information of X {\displaystyle X} relative to Y {\displaystyle Y} (which represents conceptually the average amount of information about X {\displaystyle X} that can be gained by observing Y {\displaystyle Y} ) is given by:

  7. Sample entropy - Wikipedia

    en.wikipedia.org/wiki/Sample_entropy

    Like approximate entropy (ApEn), Sample entropy (SampEn) is a measure of complexity. [1] But it does not include self-similar patterns as ApEn does. For a given embedding dimension, tolerance and number of data points, SampEn is the negative natural logarithm of the probability that if two sets of simultaneous data points of length have distance < then two sets of simultaneous data points of ...

  8. 2 Tech Stocks You Can Buy and Hold for the Next Decade

    www.aol.com/2-tech-stocks-buy-hold-110200877.html

    Image source: Getty Images. 2. Microsoft. One company that has proven to be very adaptable over the years is Microsoft (NASDAQ: MSFT).The company has long been the leader it worker productivity ...

  9. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Orange, a data mining, machine learning, and bioinformatics software; Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data