"Decision trees are a way of representing a series of rules that lead to a class or value. For example, the goal may be to classify a group of householders who have moved to a new house, based on their choice of type of the new dwelling. A simple decision tree can solve this problem and illustrate all the basic components of a decision tree (the decision nodes, branches, and leaves)." (William A V Clark & Marinus C Deurloo, "Categorical Modeling/Automatic Interaction Detection", Encyclopedia of Social Measurement, 2005)
"A decision tree is a graphical representation of various alternatives and sequence of events in these multi-stage decision problems." (P C Tulsian and Vishal Pandey, "Quantitative Techniques: Theory and Problems", 2006)
"A representation of a hierarchical set of rules that lead to sets of observations based on the class or value of the response variable." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)
"A decision-making method that uses a branch diagram to portray different options and outcomes." (Steven Haines, "The Product Manager's Desk Reference", 2008)
"It is technique for classifying data. The root node of a decision tree represents all examples. If these examples belong to two or more classes, then the most discriminating attribute is selected and the set is split into multiple classes." (Indranil Bose, "Data Mining in Tourism", 2009)
"A graph of decisions and their possible consequences (including resource costs and risks) used to create a plan to reach a goal. Decision trees are constructed in order to help with making decisions. A decision tree is a special form of tree structure. Regression trees approximate real-valued functions (e.g., estimate the price of a house or a patient's length of stay in a hospital). Classification trees define the logic for categorization using Boolean variables such as gender (male or female) or game results (lose or win)." (DAMA International, "The DAMA Dictionary of Data Management", 2011)
"A treelike model of data produced by certain data mining methods. Decision trees can be used for prediction." (Microsoft, "SQL Server 2012 Glossary", 2012)
"A graphic tool for specifying the action that will result from each combination of a set of conditions." (James Robertson et al, "Complete Systems Analysis: The Workbook, the Textbook, the Answers", 2013)
"An algorithm that focuses on maximizing group separation by iteratively splitting variables." (Evan Stubbs, "Delivering Business Analytics: Practical Guidelines for Best Practice", 2013)
"Decision trees are decision support models that classify patterns using a sequence of well-defined rules. They are tree-like graphs in which each branch node represents an option between a number of alternatives, and each leaf node represents an outcome of the cumulative choices." (Joo Chuan Tong & Shoba Ranganathan, "Computational T cell vaccine design", Computer-Aided Vaccine Design, 2013)
"The Decision Tree is a form of flow diagram that helps to map out complicated decision-making processes, or the possible directions a conversation or interaction might take." (Kevin Duncan, "The Diagrams Book", 2013)
"A family of classification methods whose results are usually represented in a tree-like graph." (Meta S Brown, "Data Mining For Dummies", 2014)
"A tool to help make decisions based on a set of rules that help to navigate the tree along its branches." (Sanjiv K Bhatia & Jitender S Deogun, "Data Mining Tools: Association Rules", 2014)
"An algorithm that focuses on maximizing group separation by iteratively splitting variables." (Evan Stubbs, "Big Data, Big Innovation", 2014)
"A representation of knowledge in a tree-like form usually
used for classification. The non-terminal nodes of the tree represent
questions, the terminal nodes represent class labels and the edges represent
answers to questions." (Petr Berka, "Machine Learning", 2015)
"Decision tree learning is a supervised machine learning technique for inducing a decision tree from training data. A decision tree (also referred to as a classification tree or a reduction tree) is a predictive model which is a mapping from observations about an item to conclusions about its target value." (Lin Tan, "The Art and Science of Analyzing Software Data", 2015)
"A simple decision tree is an algorithm for determining a decision by making a sequence of logical or property tests." (Robert J Glushko, "The Discipline of Organizing: Professional Edition" 4th Ed., 2016)
"An organised pathway of ideas leading to a defined goal, in which at various points, a decision is made about which of two ‘branches’ of ideas to follow to the next decision point." (K N Krishnaswamy et al, "Management Research Methodology: Integration of Principles, Methods and Techniques", 2016)
"A decision tree is a largely used non-parametric effective machine learning modeling technique for regression and classification problems." (Thomas Plapinger, "What is a Decision Tree", 2017)
"A decision tree is the arrangement of data in a tree structure where, at each node, data is separated into different branches according to the value of the attribute at the node." (David Natingga, "Data Science Algorithms in a Week" 2nd Ed., 2018)
"A model classifying a data item into one of the classes at the leaf node, based on matching properties between the branches on the tree and the actual data item." (David Natingga, "Data Science Algorithms in a Week" 2nd Ed., 2018)
"Decision tree is a technique that helps us in deriving rules from data. A rule-based technique is very helpful in explaining how the model is supposed to work in estimating a dependent variable value." (V Kishore Ayyadevara et al, "Hands-On Machine Learning on Google Cloud Platform", 2018)
"Decision trees are a machine learning algorithm that predicts the value of a target variable based on decision rules learned from training data. The algorithm can be applied to both regression and classification problems by changing the objective function that governs how the tree learns the decision rules." (Stefan Jansen, "Hands-On Machine Learning for Algorithmic Trading", 2018)
"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." (James D Miller, "Hands-On Machine Learning with IBM Watson", 2019)
"In a machine learning context, a decision tree is a data structure that is built for classification or regression tasks. Each node in the tree splits on a particular feature." (Alex Thomas, "Natural Language Processing with Spark NLP", 2020)
"A decision tree is a graph that uses a branching method to illustrate every possible outcome of a decision." (WhatIs) [source]
"A tree and branch-based model, like a flow chart, used to map decisions and their possible consequences. The decision tree is widely used in machine learning for classification and regression algorithms." (Accenture)
"A treelike model of data produced by certain data mining methods." (Microsoft Technet)
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