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1. www.geeksforgeeks.org › decision-treeDecision Tree - GeeksforGeeks

   www.geeksforgeeks.org › decision-tree

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   May 17, 2024 · Learn what decision trees are, how they work, and their advantages and disadvantages. Find out how to create, prune, and apply decision trees in various fields such as machine learning, data mining, and statistics.

   • Video Duration: 19 min

2. scikit-learn.org › stable › modules1.10. Decision Trees — scikit-learn 1.5.1 documentation

   scikit-learn.org › stable › modules

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   Learn how to use decision trees for classification and regression with scikit-learn, a Python machine learning library. Decision trees are non-parametric models that learn simple decision rules from data features.

3. www.javatpoint.com › machine-learning-decisionDecision Tree Algorithm in Machine Learning - Javatpoint

   www.javatpoint.com › machine-learning-decision

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   Learn how to use decision tree, a supervised learning technique, for classification and regression problems. Understand the terminologies, steps, and techniques of decision tree, such as information gain, Gini index, and pruning.

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4. en.wikipedia.org › wiki › Decision_treeDecision tree - Wikipedia

   en.wikipedia.org › wiki › Decision_tree

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   A decision tree is a decision support hierarchical model 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.

5. www.analyticsvidhya.com › decision-tree-algorithmDecision Tree? [A Step-by-Step Guide] - Analytics Vidhya

   www.analyticsvidhya.com › decision-tree-algorithm

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   May 31, 2024 · Learn what a decision tree is, how it works, and how to build and optimize it for classification and regression tasks. This guide covers the terminology, assumptions, and applications of decision trees with examples and diagrams.

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6. www.ibm.com › topics › decision-treesWhat is a Decision Tree? | IBM

   www.ibm.com › topics › decision-trees

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   Learn what a decision tree is, how it works, and why it is used for classification and regression tasks. Explore different types of decision tree algorithms, such as ID3, C4.5 and CART, and how to choose the best attribute to split on.

7. People also ask

   What is a decision tree structure?

   • It has a hierarchical, tree structure, which consists of a root node, branches, internal nodes and leaf nodes. As you can see from the diagram below, a decision tree starts with a root node, which does not have any incoming branches.

   What is a Decision Tree? | IBM

   www.ibm.com/topics/decision-trees

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   What is a root node in a decision tree?

   • Root Node: The initial node at the beginning of a decision tree, where the entire population or dataset starts dividing based on various features or conditions. Decision Nodes: Nodes resulting from the splitting of root nodes are known as decision nodes. These nodes represent intermediate decisions or conditions within the tree.

   Decision Tree? [A Step-by-Step Guide] - Analytics Vidhya

   www.analyticsvidhya.com/blog/2021/08/decision-tree-algorithm/

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   How does a decision tree work?

   • In a decision tree, for predicting the class of the given dataset, the algorithm starts from the root node of the tree. This algorithm compares the values of root attribute with the record (real dataset) attribute and, based on the comparison, follows the branch and jumps to the next node.

   Decision Tree Algorithm in Machine Learning - Javatpoint

   www.javatpoint.com/machine-learning-decision-tree-classification-algorithm

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   What are decision trees used for?

   • Decision trees are used for classification and regression tasks, providing easy-to-understand models. A decision tree is a hierarchical model used in decision support that depicts decisions and their potential outcomes, incorporating chance events, resource expenses, and utility.

   Decision Tree? [A Step-by-Step Guide] - Analytics Vidhya

   www.analyticsvidhya.com/blog/2021/08/decision-tree-algorithm/

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8. towardsdatascience.com › understanding-decisionUnderstanding Decision Trees (once and for all!) | by ...

   towardsdatascience.com › understanding-decision

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   Mar 2, 2019 · In this article, we dissected Decision Trees to understand every concept behind the building of this algorithm that is a must know. 👏 To understand how a Decision Tree is built, we took a concrete example : the iris dataset made up of continuous features and a categorical target. Decision Trees can also be built using categorical features ...