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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 ...
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.
The problem of learning an optimal decision tree is known to be NP-complete under several aspects of optimality and even for simple concepts. [35] [36] 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 ...
The following table lists many common symbols, together with their name, how they should be read out loud, and the related field of mathematics. Additionally, the subsequent columns contains an informal explanation, a short example, the Unicode location, the name for use in HTML documents, [1] and the LaTeX symbol.
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.
Monte Carlo methods have been developed into a technique called Monte-Carlo tree search that is useful for searching for the best move in a game. Possible moves are organized in a search tree and many random simulations are used to estimate the long-term potential of each move. A black box simulator represents the opponent's moves.
Tree diagram (probability theory), a diagram to represent a probability space in probability theory; Decision tree, a decision support tool that uses a tree-like graph or model of decisions and their possible consequences; Event tree, inductive analytical diagram in which an event is analyzed using Boolean logic
Information gain (decision tree) Information gain ratio; L. Logistic model tree; R. Random forest