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  2. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    where ⁡ is the interquartile range of the data and is the number of observations in the sample . In fact if the normal density is used the factor 2 in front comes out to be ∼ 2.59 {\displaystyle \sim 2.59} , [ 4 ] but 2 is the factor recommended by Freedman and Diaconis.

  3. Spearman's rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Spearman's_rank_correlation...

    This method is applicable to stationary streaming data as well as large data sets. For non-stationary streaming data, where the Spearman's rank correlation coefficient may change over time, the same procedure can be applied, but to a moving window of observations. When using a moving window, memory requirements grow linearly with chosen window ...

  4. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    Data orientation is the representation of tabular data in a linear memory model such as in-disk or in-memory. The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...

  5. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  6. Secretary problem - Wikipedia

    en.wikipedia.org/wiki/Secretary_problem

    Graphs of probabilities of getting the best candidate (red circles) from n applications, and k/n (blue crosses) where k is the sample size. The secretary problem demonstrates a scenario involving optimal stopping theory [1] [2] that is studied extensively in the fields of applied probability, statistics, and decision theory.

  7. Move-to-front transform - Wikipedia

    en.wikipedia.org/wiki/Move-to-front_transform

    The move-to-front (MTF) transform is an encoding of data (typically a stream of bytes) designed to improve the performance of entropy encoding techniques of compression. When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithm .

  8. BED (file format) - Wikipedia

    en.wikipedia.org/wiki/BED_(file_format)

    These columns must be separated by spaces or tabs, the latter being recommended for reasons of compatibility between programs. [6] Each row of a file must have the same number of columns. The order of the columns must be respected: if columns of high numbers are used, the columns of intermediate numbers must be filled in.

  9. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    The table is easy to construct one row at a time starting with row 0. When the entire table has been built, the desired distance is in the table in the last row and column, representing the distance between all of the characters in s and all the characters in t .