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  2. Comparison of programming languages (string functions ...

    en.wikipedia.org/wiki/Comparison_of_programming...

    Returns the position of the start of the last occurrence of substring in string. If the substring is not found most of these routines return an invalid index value – -1 where indexes are 0-based, 0 where they are 1-based – or some value to be interpreted as Boolean FALSE. Related instr

  3. MCS algorithm - Wikipedia

    en.wikipedia.org/wiki/MCS_algorithm

    The boxes are then iteratively split along an axis plane according to the value of the function at a representative point of the box (and its neighbours) and the box's size. These two splitting criteria combine to form a global search by splitting large boxes and a local search by splitting areas for which the function value is good.

  4. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.

  5. R*-tree - Wikipedia

    en.wikipedia.org/wiki/R*-tree

    When splitting, the R*-tree uses a topological split that chooses a split axis based on perimeter, then minimizes overlap. In addition to an improved split strategy, the R*-tree also tries to avoid splits by reinserting objects and subtrees into the tree, inspired by the concept of balancing a B-tree .

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Foreach loop - Wikipedia

    en.wikipedia.org/wiki/Foreach_loop

    Python's tuple assignment, fully available in its foreach loop, also makes it trivial to iterate on (key, value) pairs in dictionaries: for key , value in some_dict . items (): # Direct iteration on a dict iterates on its keys # Do stuff

  8. Circuit satisfiability problem - Wikipedia

    en.wikipedia.org/wiki/Circuit_satisfiability_problem

    A split gadget. This gadget guarantees that all the output wires have the same value as the input wire. Gadgets simulating the gates of the circuit. A True terminator gadget. This gadget is used to force the output of the entire circuit to be True. A turn gadget. This gadget allows us to redirect wires in the right direction as needed. A ...

  9. Skew heap - Wikipedia

    en.wikipedia.org/wiki/Skew_heap

    Split each heap into subtrees by cutting every path. (From the root node, sever the right node and make the right child its own subtree.) This will result in a set of trees in which the root either only has a left child or no children at all. Sort the subtrees in ascending order based on the value of the root node of each subtree.