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  2. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    In decision tree learning, greedy algorithms are commonly used, however they are not guaranteed to find the optimal solution. One popular such algorithm is the ID3 algorithm for decision tree construction. Dijkstra's algorithm and the related A* search algorithm are verifiably optimal greedy algorithms for graph search and shortest path finding.

  3. Beam search - Wikipedia

    en.wikipedia.org/wiki/Beam_search

    Beam search is a modification of best-first search that reduces its memory requirements. Best-first search is a graph search which orders all partial solutions (states) according to some heuristic. But in beam search, only a predetermined number of best partial solutions are kept as candidates. [1] It is thus a greedy algorithm.

  4. Best-first search - Wikipedia

    en.wikipedia.org/wiki/Best-first_search

    Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...

  5. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    What sets A* apart from a greedy best-first search algorithm is that it takes the cost/distance already traveled, g(n), into account. Some common variants of Dijkstra's algorithm can be viewed as a special case of A* where the heuristic h ( n ) = 0 {\displaystyle h(n)=0} for all nodes; [ 12 ] [ 13 ] in turn, both Dijkstra and A* are special ...

  6. Category:Greedy algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Greedy_algorithms

    Greedy number partitioning; Greedy randomized adaptive search procedure; K. Kruskal's algorithm; P. Prim's algorithm

  7. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    The problem of learning an optimal decision tree is known to be NP-complete under several aspects of optimality and even for simple concepts. [34] [35] Consequently, practical decision-tree learning algorithms are based on heuristics such as the greedy algorithm where locally optimal decisions are made at each node. Such algorithms cannot ...

  8. Google responds to Elon Musk’s accusations of a ‘search ban ...

    www.aol.com/finance/google-responds-elon-musk...

    Google has responded to Elon Musk, Donald Trump Jr., and other top GOP figures’ accusations that the search engine is interfering in the election with its auto-complete results.. On Sunday ...

  9. Graph traversal - Wikipedia

    en.wikipedia.org/wiki/Graph_traversal

    In computer science, graph traversal (also known as graph search) refers to the process of visiting (checking and/or updating) each vertex in a graph. Such traversals are classified by the order in which the vertices are visited. Tree traversal is a special case of graph traversal.