enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Alternating decision tree - Wikipedia

    en.wikipedia.org/wiki/Alternating_decision_tree

    Original boosting algorithms typically used either decision stumps or decision trees as weak hypotheses. As an example, boosting decision stumps creates a set of weighted decision stumps (where is the number of boosting iterations), which then vote on the final classification according to their weights. Individual decision stumps are weighted ...

  3. 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 ...

  4. C4.5 algorithm - Wikipedia

    en.wikipedia.org/wiki/C4.5_algorithm

    This algorithm has a few base cases. All the samples in the list belong to the same class. When this happens, it simply creates a leaf node for the decision tree saying to choose that class. None of the features provide any information gain. In this case, C4.5 creates a decision node higher up the tree using the expected value of the class.

  5. Decision tree - Wikipedia

    en.wikipedia.org/wiki/Decision_tree

    The node splitting function used can have an impact on improving the accuracy of the decision tree. For example, using the information-gain function may yield better results than using the phi function. The phi function is known as a measure of “goodness” of a candidate split at a node in the decision tree.

  6. 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.

  7. ID3 algorithm - Wikipedia

    en.wikipedia.org/wiki/ID3_algorithm

    In decision tree learning, ID3 (Iterative Dichotomiser 3) is an algorithm invented by Ross Quinlan [1] used to generate a decision tree from a dataset. ID3 is the precursor to the C4.5 algorithm , and is typically used in the machine learning and natural language processing domains.

  8. NFL approves adjustment to playoff rules, resulting in ... - AOL

    www.aol.com/sports/nfl-owners-approve-playoff...

    The decision to allow the Bills and Bengals to complete 2022-23 with a 16-game schedule now places specific AFC title game qualifiers on those two teams for only the 2022-23 season.

  9. Category:Decision trees - Wikipedia

    en.wikipedia.org/wiki/Category:Decision_trees

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more