A decision tree is a decision support recursive partitioning structure that uses a tree-like model of decisions and their possible consequences, including...

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or...

learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances...

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...

typically simple decision trees. When a decision tree is the weak learner, the resulting algorithm is called gradient-boosted trees; it usually outperforms...

Game tree size (total number of possible games) Decision complexity (number of leaf nodes in the smallest decision tree for initial position) Game-tree complexity...

An alternating decision tree (ADTree) is a machine learning method for classification. It generalizes decision trees and has connections to boosting....

In the context of decision trees in information theory and machine learning, information gain refers to the conditional expected value of the Kullback–Leibler...

An incremental decision tree algorithm is an online machine learning algorithm that outputs a decision tree. Many decision tree methods, such as C4.5,...

A decision model in decision theory is the starting point for a decision method within a formal (axiomatic) system. Decision models contain at least one...

analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data...

decision forests is an ensemble learning method for classification, regression and other tasks that works by creating a multitude of decision trees during...

A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected, edge-weighted undirected graph that connects all...

by decision analysts with an intuitive semantic that is easy to understand. It is now adopted widely and becoming an alternative to the decision tree which...

(like random decision trees) can be used to produce a stronger ensemble than very deliberate algorithms (like entropy-reducing decision trees). Using a variety...

take the form of a decision tree Decision tree model#Quantum decision tree, decision tree complexity for a quantum decision tree Equitable cake-cutting#Query...

reduces variance and overfitting. Although it is usually applied to decision tree methods, it can be used with any type of method. Bagging is a special...

{\displaystyle f(0,1,1)} . The binary decision tree of the left figure can be transformed into a binary decision diagram by maximally reducing it according...

BSP tree Rapidly exploring random tree Abstract syntax tree Parse tree Decision tree Alternating decision tree Minimax tree Expectiminimax tree Finger...

process of adding nodes to inferred decision trees to improve the predictive accuracy.[clarification needed] A decision tree is a graphical model that is used...

two types: Multi-relational decision tree learning (MRDTL) uses a supervised algorithm that is similar to a decision tree. Deep Feature Synthesis uses...

specified by a k-length decision list includes as a subset the language specified by a k-depth decision tree. Learning decision lists can be used for attribute...

subtree that can be used to solve the game is known as a decision tree, and the sizes of decision trees of various shapes are used as measures of game complexity...

In decision tree learning, ID3 (Iterative Dichotomiser 3) is an algorithm invented by Ross Quinlan used to generate a decision tree from a dataset. ID3...

a single decision tree, it sacrifices the intrinsic interpretability of decision trees.  For example, following the path that a decision tree takes to...

deterministic decision trees, and for any k in the range 2 ≤ k ≤ n, the property of containing a k-clique was shown to have decision tree complexity exactly...

exists resources regarding adaptive management decision cycles. Adaptive management Decision tree Decisional balance sheet Feedback Learning cycle Systems...

in a comparison-based model of computation such as a decision tree or algebraic decision tree, is Θ ( n log ⁡ n ) {\displaystyle \Theta (n\log n)} ....

science) Trees can also be represented radially: Kinds of trees B-tree Dancing tree Decision tree Left-child right-sibling binary tree Porphyrian tree Tree (data...

isolated using few partitions. Like decision tree algorithms, it does not perform density estimation. Unlike decision tree algorithms, it uses only path length...