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  2. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    An example of such is the classic merge that appears frequently in merge sort examples. The classic merge outputs the data item with the lowest key at each step; given some sorted lists, it produces a sorted list containing all the elements in any of the input lists, and it does so in time proportional to the sum of the lengths of the input lists.

  3. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.

  4. Merge (linguistics) - Wikipedia

    en.wikipedia.org/wiki/Merge_(linguistics)

    In terms of a merge-base theory of language acquisition, complements and specifiers are simply notations for first-merge (read as "complement-of" [head-complement]), and later second-merge (read as "specifier-of" [specifier-head]), with merge always forming to a head. First-merge establishes only a set {a, b} and is not an ordered pair.

  5. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and produces a vector space , typically of several hundred dimensions , with each unique word in the corpus being assigned a corresponding vector in the space.

  6. Merge sort - Wikipedia

    en.wikipedia.org/wiki/Merge_sort

    In computer science, merge sort (also commonly spelled as mergesort and as merge-sort [2]) is an efficient, general-purpose, and comparison-based sorting algorithm.Most implementations produce a stable sort, which means that the relative order of equal elements is the same in the input and output.

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    A scatterplot illustrating the correlation between two variables (inflation and unemployment) measured at points in time. Stephen Few described eight types of quantitative messages that users may attempt to understand or communicate from a set of data and the associated graphs used to help communicate the message. [ 48 ]

  8. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Python, an open-source programming language widely used in data mining and machine learning. R, an open-source programming language for statistical computing and graphics. Together with Python one of the most popular languages for data science. TinkerPlots an EDA software for upper elementary and middle school students.

  9. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    This plane is also defined by the first two PCA dimensions. Well-separated clusters are effectively modelled by ball-shaped clusters and thus discovered by k-means. Non-ball-shaped clusters are hard to separate when they are close. For example, two half-moon shaped clusters intertwined in space do not separate well when projected onto PCA subspace.