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  2. 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 ...

  3. BED (file format) - Wikipedia

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

    A BED file consists of a minimum of three columns to which nine optional columns can be added for a total of twelve columns. The first three columns contain the names of chromosomes or scaffolds, the start, and the end coordinates of the sequences considered. The next nine columns contain annotations related to these sequences.

  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. 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 .

  7. 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 .

  8. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    Once the t value and degrees of freedom are determined, a p-value can be found using a table of values from Student's t-distribution. If the calculated p -value is below the threshold chosen for statistical significance (usually the 0.10, the 0.05, or 0.01 level), then the null hypothesis is rejected in favor of the alternative hypothesis.

  9. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Given a twice continuously differentiable function of one real variable, Taylor's theorem for the case = states that = + ′ () + where is the remainder term. The linear approximation is obtained by dropping the remainder: () + ′ ().