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Decision tree learning

Index Decision tree learning

Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). [1]

60 relations: AdaBoost, Alternating decision tree, Artificial neural network, Binary decision diagram, Black box, Bootstrap aggregating, C4.5 algorithm, Categorical variable, Chi-square automatic interaction detection, Classification chart, Data mining, Decision list, Decision stump, Decision tree, Decision tree learning, Decision-making, Directed acyclic graph, Dummy variable (statistics), Entropy (information theory), Feature (machine learning), Gradient boosting, Greedy algorithm, Hierarchical clustering, ID3 algorithm, Incremental decision tree, Information gain in decision trees, Information theory, KNIME, Leo Breiman, Logical conjunction, Logistic model tree, Machine learning, Markov chain Monte Carlo, MATLAB, Microsoft SQL Server, Minimum message length, Multivariate adaptive regression splines, NP-completeness, Orange (software), Overfitting, Predictive modelling, Principal component analysis, Pruning (decision trees), Python (programming language), R (programming language), Random forest, RapidMiner, Real number, Recursion, Recursive partitioning, ..., Scikit-learn, Set (mathematics), SPSS Modeler, Statistics, Structured data analysis (statistics), Tree (data structure), Umbrella term, Variance, Weka (machine learning), White box (software engineering). Expand index (10 more) »

AdaBoost

AdaBoost, short for Adaptive Boosting, is a machine learning meta-algorithm formulated by Yoav Freund and Robert Schapire, who won the 2003 Gödel Prize for their work.

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Alternating decision tree

An alternating decision tree (ADTree) is a machine learning method for classification.

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Artificial neural network

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.

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Binary decision diagram

In computer science, a binary decision diagram (BDD) or branching program is a data structure that is used to represent a Boolean function.

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Black box

In science, computing, and engineering, a black box is a device, system or object which can be viewed in terms of its inputs and outputs (or transfer characteristics), without any knowledge of its internal workings.

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Bootstrap aggregating

Bootstrap aggregating, also called bagging, is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regression.

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C4.5 algorithm

C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan.

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Categorical variable

In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property.

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Chi-square automatic interaction detection

Chi-square automatic interaction detection (CHAID) is a decision tree technique, based on adjusted significance testing (Bonferroni testing).

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Classification chart

Classification chart or classification tree is a synopsis of the classification scheme, designed to illustrate the structure of any particular field.

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Data mining

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

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Decision list

Decision lists are a representation for Boolean functions which can be easily learnable from examples.

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Decision stump

A decision stump is a machine learning model consisting of a one-level decision tree.

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Decision tree

A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.

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Decision tree learning

Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves).

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Decision-making

In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities.

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Directed acyclic graph

In mathematics and computer science, a directed acyclic graph (DAG), is a finite directed graph with no directed cycles.

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Dummy variable (statistics)

In statistics and econometrics, particularly in regression analysis, a dummy variable (also known as an indicator variable, design variable, Boolean indicator, binary variable, or qualitative variable) is one that takes the value 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.

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Entropy (information theory)

Information entropy is the average rate at which information is produced by a stochastic source of data.

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Feature (machine learning)

In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon being observed.

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Gradient boosting

Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.

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Greedy algorithm

A greedy algorithm is an algorithmic paradigm that follows the problem solving heuristic of making the locally optimal choice at each stage with the intent of finding a global optimum.

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Hierarchical clustering

In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters.

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ID3 algorithm

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

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Incremental decision tree

An incremental decision tree algorithm is an online machine learning algorithm that outputs a decision tree.

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Information gain in decision trees

In information theory and machine learning, information gain is a synonym for Kullback–Leibler divergence.

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Information theory

Information theory studies the quantification, storage, and communication of information.

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KNIME

KNIME, the Konstanz Information Miner, is a free and open-source data analytics, reporting and integration platform.

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Leo Breiman

Leo Breiman (January 27, 1928 – July 5, 2005) was a distinguished statistician at the University of California, Berkeley.

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Logical conjunction

In logic, mathematics and linguistics, And (∧) is the truth-functional operator of logical conjunction; the and of a set of operands is true if and only if all of its operands are true.

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Logistic model tree

In computer science, a logistic model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic regression (LR) and decision tree learning.

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Machine learning

Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

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Markov chain Monte Carlo

In statistics, Markov chain Monte Carlo (MCMC) methods comprise a class of algorithms for sampling from a probability distribution.

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MATLAB

MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks.

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Microsoft SQL Server

Microsoft SQL Server is a relational database management system developed by Microsoft.

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Minimum message length

Minimum message length (MML) is a formal information theory restatement of Occam's Razor: even when models are equal in goodness of fit accuracy to the observed data, the one generating the shortest overall message is more likely to be correct (where the message consists of a statement of the model, followed by a statement of data encoded concisely using that model).

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Multivariate adaptive regression splines

In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991.

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NP-completeness

In computational complexity theory, an NP-complete decision problem is one belonging to both the NP and the NP-hard complexity classes.

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Orange (software)

Orange is an open-source data visualization, machine learning and data mining toolkit.

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Overfitting

In statistics, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably".

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Predictive modelling

Predictive modelling uses statistics to predict outcomes.

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Principal component analysis

Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.

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Pruning (decision trees)

Pruning is a technique in machine learning that reduces the size of decision trees by removing sections of the tree that provide little power to classify instances.

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Python (programming language)

Python is an interpreted high-level programming language for general-purpose programming.

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R (programming language)

R is a programming language and free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing.

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Random forest

Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.

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RapidMiner

RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.

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Real number

In mathematics, a real number is a value of a continuous quantity that can represent a distance along a line.

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Recursion

Recursion occurs when a thing is defined in terms of itself or of its type.

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Recursive partitioning

Recursive partitioning is a statistical method for multivariable analysis.

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Scikit-learn

Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language.

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Set (mathematics)

In mathematics, a set is a collection of distinct objects, considered as an object in its own right.

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SPSS Modeler

IBM SPSS Modeler is a data mining and text analytics software application from IBM.

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Statistics

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

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Structured data analysis (statistics)

Structured data analysis is the statistical data analysis of structured data.

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Tree (data structure)

In computer science, a tree is a widely used abstract data type (ADT)—or data structure implementing this ADT—that simulates a hierarchical tree structure, with a root value and subtrees of children with a parent node, represented as a set of linked nodes.

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Umbrella term

An umbrella term is a word or phrase that covers a wide range of concepts belonging to a common category.

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Variance

In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean.

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Weka (machine learning)

Waikato Environment for Knowledge Analysis (Weka) is a suite of machine learning software written in Java, developed at the University of Waikato, New Zealand.

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White box (software engineering)

A white box (or glass box, clear box, or open box) is a subsystem whose internals can be viewed but usually not altered.

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Classification and Regression Tree, Classification and regression tree, Decision Tree Learning, Decision Tree Training, Decision Tree Training Algorithm, Decision tree training, Gini impurity, Regression tree.

References

[1] https://en.wikipedia.org/wiki/Decision_tree_learning

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