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Classification and Regression Trees
Classification and Regression Trees

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!!! Overview
[{$pagename}] ([CART]) analysis is an umbrella term used to refer to both:
* [Classification Trees]
* [Regression Trees]
The [{$pagename}] [algorithm] is structured as a sequence of questions, the answers to which determine what the next question, if any should be. The result of these questions is a tree like structure where the ends are terminal nodes at which point there are no more questions.
The main elements of [{$pagename}] (and any decision tree [algorithm]) are:
* Rules for splitting data at a node based on the value of one variable;
* Stopping rules for deciding when a branch is terminal and can be split no more; and
* Finally, a [Predictor variable] for the target variable in each terminal node.
!! Example [{$pagename}]
Given a dataset with two inputs (x) of height in centimeters and weight in kilograms the output of sex as male or female, below is a crude [example] of a [binary] decision tree (completely fictitious for demonstration purposes only).
[Classification and Regression Trees/Example-Decision-Tree.png]
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
----
* [#1] - [Decision tree learning|Wikipedia:Decision_tree_learning|target='_blank'] - based on information obtained 2017-12-31
* [#2] - [Classification And Regression Trees for Machine Learning|https://machinelearningmastery.com/classification-and-regression-trees-for-machine-learning/|target='_blank'] - based on information obtained 2017-12-31-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop