Decision tree information

A decision tree is a decision support hierarchical model that uses a tree-like model of decisions and their possible consequences, including chance event...

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...

computational complexity the decision tree model is the model of computation in which an algorithm is considered to be basically a decision tree, i.e., a sequence...

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

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

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

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

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...

or average prediction of the individual trees is returned. Random decision forests correct for decision trees' habit of overfitting to their training...

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

A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management...

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

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

variance and helps to avoid 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...

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

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

set of actions. The information expressed in decision tables could also be represented as decision trees or in a programming language as a series of if-then-else...

example, the engineer may choose to use support-vector machines or decision trees. Complete the design. Run the learning algorithm on the gathered training...

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...

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...

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...

machine learning, originally developed by Microsoft. It is based on decision tree algorithms and used for ranking, classification and other machine learning...

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)} ....

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...

2018-10-06. Issue trees, issue maps, logic trees, how trees, why trees, diagnostic trees, solution trees, decision trees, fact trees, hypothesis trees... How should...