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  2. Ranking - Wikipedia

    en.wikipedia.org/wiki/Ranking

    For v = 1.0, the fractional rank is the average of the ordinal ranks: (1 + 2) / 2 = 1.5. In a similar manner, for v = 5.0, the fractional rank is (7 + 8 + 9) / 3 = 8.0. Thus the fractional ranks are: 1.5, 1.5, 3.0, 4.5, 4.5, 6.0, 8.0, 8.0, 8.0 This method is called "Mean" by IBM SPSS [4] and "average" by the R programming language [5] in their ...

  3. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    In machine learning, a ranking SVM is a variant of the support vector machine algorithm, which is used to solve certain ranking problems (via learning to rank).The ranking SVM algorithm was published by Thorsten Joachims in 2002. [1]

  4. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    This yields an average time complexity of O(n log n), with low overhead, and thus this is a popular algorithm. Efficient implementations of quicksort (with in-place partitioning) are typically unstable sorts and somewhat complex but are among the fastest sorting algorithms in practice.

  5. PageRank - Wikipedia

    en.wikipedia.org/wiki/PageRank

    The SERP rank of a web page refers to the placement of the corresponding link on the SERP, where higher placement means higher SERP rank. The SERP rank of a web page is a function not only of its PageRank, but of a relatively large and continuously adjusted set of factors (over 200).

  6. Ranking (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Ranking_(information...

    Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.

  7. Quantile normalization - Wikipedia

    en.wikipedia.org/wiki/Quantile_normalization

    In the case of column 2, they represent ranks iii and iv. So we assign the two tied rank iii entries the average of rank iii and rank iv ((4.67 + 5.67)/2 = 5.17). And so we arrive at the following set of normalized values:

  8. Order statistic tree - Wikipedia

    en.wikipedia.org/wiki/Order_statistic_tree

    Rank(x) – find the rank of element x in the tree, i.e. its index in the sorted list of elements of the tree; Both operations can be performed in O(log n) worst case time when a self-balancing tree is used as the base data structure.

  9. Selection algorithm - Wikipedia

    en.wikipedia.org/wiki/Selection_algorithm

    A notable exception is the Standard Template Library for C++, which provides a templated nth_element method with a guarantee of expected linear time. [3] Python's standard library includes heapq.nsmallest and heapq.nlargest functions for returning the smallest or