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  2. Flattening transformation - Wikipedia

    en.wikipedia.org/wiki/Flattening_transformation

    The flattening transformation is an algorithm that transforms nested data parallelism into flat data parallelism. It was pioneered by Guy Blelloch as part of the NESL programming language. [ 1 ] The flattening transformation is also sometimes called vectorization , but is completely unrelated to automatic vectorization .

  3. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.

  4. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Even though the row is indicated by the first index and the column by the second index, no grouping order between the dimensions is implied by this. The choice of how to group and order the indices, either by row-major or column-major methods, is thus a matter of convention. The same terminology can be applied to even higher dimensional arrays.

  5. Multi-index notation - Wikipedia

    en.wikipedia.org/wiki/Multi-index_notation

    An n-dimensional multi-index is an -tuple = (,, …,) of non-negative integers (i.e. an element of the -dimensional set of natural numbers, denoted ).. For multi ...

  6. Inverted index - Wikipedia

    en.wikipedia.org/wiki/Inverted_index

    In computer science, an inverted index (also referred to as a postings list, postings file, or inverted file) is a database index storing a mapping from content, such as words or numbers, to its locations in a table, or in a document or a set of documents (named in contrast to a forward index, which maps from documents to content). [1]

  7. Graph flattenability - Wikipedia

    en.wikipedia.org/wiki/Graph_flattenability

    Flattenability in some -dimensional normed vector space is a property of graphs which states that any embedding, or drawing, of the graph in some high dimension ′ can be "flattened" down to live in -dimensions, such that the distances between pairs of points connected by edges are preserved.

  8. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

  9. Flat-file database - Wikipedia

    en.wikipedia.org/wiki/Flat-file_database

    Example of a flat file model [1] A flat-file database is a database stored in a file called a flat file. Records follow a uniform format, and there are no structures for indexing or recognizing relationships between records. The file is simple. A flat file can be a plain text file (e.g. csv, txt or tsv), or a binary file. Relationships can be ...