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  2. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    This process of top-down induction of decision trees (TDIDT) [5] is an example of a greedy algorithm, and it is by far the most common strategy for learning decision trees from data. [ 6 ] In data mining , decision trees can be described also as the combination of mathematical and computational techniques to aid the description, categorization ...

  3. Decision tree model - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_model

    Decision Tree Model. In computational complexity theory, the decision tree model is the model of computation in which an algorithm can be considered to be a decision tree, i.e. a sequence of queries or tests that are done adaptively, so the outcome of previous tests can influence the tests performed next.

  4. Decision tree - Wikipedia

    en.wikipedia.org/wiki/Decision_tree

    Decision trees can also be seen as generative models of induction rules from empirical data. An optimal decision tree is then defined as a tree that accounts for most of the data, while minimizing the number of levels (or "questions"). [8] Several algorithms to generate such optimal trees have been devised, such as ID3/4/5, [9] CLS, ASSISTANT ...

  5. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    An upper bound for a decision-tree model was given by Meyer auf der Heide [17] who showed that for every n there exists an O(n 4)-deep linear decision tree that solves the subset-sum problem with n items. Note that this does not imply any upper bound for an algorithm that should solve the problem for any given n.

  6. Backward induction - Wikipedia

    en.wikipedia.org/wiki/Backward_induction

    For example, in the first subgame, the choice "go to movie" offers a payoff of 9 since the decision tree terminates at the reward (9, 11), considering Player 2's previously established choice. Meanwhile, "stay home" offers a payoff of 1 since it ends at (1, 9), so Player 1 would choose "go to movie."

  7. 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.

  8. Today's Wordle Hint, Answer for #1262 on Monday, December 2, 2024

    www.aol.com/todays-wordle-hint-answer-1262...

    December 1, 2024 at 9:04 PM If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle 1262 ahead. Let's start with a few hints.

  9. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    For example, the minimum spanning tree of the graph associated with an instance of the Euclidean TSP is a Euclidean minimum spanning tree, and so can be computed in expected O(n log n) time for n points (considerably less than the number of edges). This enables the simple 2-approximation algorithm for TSP with triangle inequality above to ...

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