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  2. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    For a set of empirical measurements sampled from some probability distribution, the Freedman–Diaconis rule is designed approximately minimize the integral of the squared difference between the histogram (i.e., relative frequency density) and the density of the theoretical probability distribution.

  3. V-optimal histograms - Wikipedia

    en.wikipedia.org/wiki/V-optimal_histograms

    A v-optimal histogram is based on the concept of minimizing a quantity which is called the weighted variance in this context. [1] This is defined as = =, where the histogram consists of J bins or buckets, n j is the number of items contained in the jth bin and where V j is the variance between the values associated with the items in the jth bin.

  4. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    When plotting the histogram, the frequency density is used for the dependent axis. While all bins have approximately equal area, the heights of the histogram approximate the density distribution. For equiprobable bins, the following rule for the number of bins is suggested: [24] = /

  5. Discretization of continuous features - Wikipedia

    en.wikipedia.org/wiki/Discretization_of...

    Typically data is discretized into partitions of K equal lengths/width (equal intervals) or K% of the total data (equal frequencies). [1] Mechanisms for discretizing continuous data include Fayyad & Irani's MDL method, [2] which uses mutual information to recursively define the best bins, CAIM, CACC, Ameva, and many others [3]

  6. Bin (computational geometry) - Wikipedia

    en.wikipedia.org/wiki/Bin_(computational_geometry)

    The bin data structure. A histogram ordered into 100,000 bins. In computational geometry, the bin is a data structure that allows efficient region queries. Each time a data point falls into a bin, the frequency of that bin is increased by one.

  7. Data binning - Wikipedia

    en.wikipedia.org/wiki/Data_binning

    Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a bin , are replaced by a value representative of that interval, often a central value ( mean or median ).

  8. Entropy estimation - Wikipedia

    en.wikipedia.org/wiki/Entropy_estimation

    with bin probabilities given by that histogram. The histogram is itself a maximum-likelihood (ML) estimate of the discretized frequency distribution [citation needed]), where is the width of the th bin. Histograms can be quick to calculate, and simple, so this approach has some attraction.

  9. Bandwidth (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Bandwidth_(signal_processing)

    Baseband bandwidth is equal to the upper cutoff frequency of a low-pass filter or baseband signal, which includes a zero frequency. Bandwidth in hertz is a central concept in many fields, including electronics , information theory , digital communications , radio communications , signal processing , and spectroscopy and is one of the ...