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Grafting (decision Trees)
Grafting is the process of adding nodes to inferred decision trees to improve the predictive accuracy. A decision tree is a graphical model that is used as a support tool for decision process. Introduction Once the decision tree is constructed, then the new branches that can be added productively to the tree are identified. Then they are grafted to the existing tree to improve the decision making process. ''Pruning'' and ''Grafting'' are complementary methods to improve the decision tree in supporting the decision. Pruning allows cutting parts of decision trees to give more clarity and Grafting adds nodes to the decision trees to increase the predictive accuracy. To achieve grafting new branches can be added in the place of a single leaf or graft within leaves. Illustration The information required is given in the form of a chart as, The nodes and leaves can be identified from the given information and the decision trees are constructed. One such decision tree is as follows, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Tree
A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a decision tree and the closely related influence diagram are used as a visual and analytical decision support tool, where t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graphical Model
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a Graph (discrete mathematics), graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning. Types of graphical models Generally, probabilistic graphical models use a graph-based representation as the foundation for encoding a distribution over a multi-dimensional space and a graph that is a compact or Factor graph, factorized representation of a set of independences that hold in the specific distribution. Two branches of graphical representations of distributions are commonly used, namely, Bayesian networks and Markov random fields. Both families encompass the properties of factorization and independences, but they differ in the set of independences they can encode and the factorization of the distribution that they induce ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chart Of Random Data
A chart (sometimes known as a graph) is a graphical representation for data visualization, in which "the data is represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart". A chart can represent tabular numeric data, functions or some kinds of quality structure and provides different info. The term "chart" as a graphical representation of data has multiple meanings: * A data chart is a type of diagram or graph, that organizes and represents a set of numerical or qualitative data. * Maps that are adorned with extra information (map surround) for a specific purpose are often known as charts, such as a nautical chart or aeronautical chart, typically spread over several map sheets. * Other domain-specific constructs are sometimes called charts, such as the chord chart in music notation or a record chart for album popularity. Charts are often used to ease understanding of large quantities of data and the relationships between parts of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Tree Chart From Random Data
Decision may refer to: Law and politics *Judgment (law), as the outcome of a legal case *Landmark decision, the outcome of a case that sets a legal precedent * ''Per curiam'' decision, by a court with multiple judges Books * ''Decision'' (novel), a 1983 political novel by Allen Drury * ''The Decision'' (novel), a 1998 book in the ''Animorphs'' series Sports *Decision (baseball), a statistical credit earned by a baseball pitcher * Decisions in combat sports *Decisions (professional wrestling), by which a wrestler scores a point against his opponent Film and TV * ''Decision'' (TV series), an American anthology TV series * ''The Decision'' (play), by the 20th-century German dramatist Bertolt Brecht * ''The Decision'' (TV special), in which NBA player LeBron James announced that he would switch teams * "The Decision" (song), by English indie rock band Young Knives Music Albums * ''Decisions'' (George Adams and Don Pullen album), 1984 * ''Decisions'' (The Winans album), 1987 Songs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision-tree Grafting
A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a decision tree and the closely related influence diagram are used as a visual and analytical decision support tool, where the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
