Computer Science
决策树
Decision TreeA decision tree is a predictive modeling tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one of the most fundamental and widely used algorithms in machine learning for classification and regression tasks. / 决策树是一种预测建模工具，使用树状图或决策模型及其可能后果，包括机会事件结果、资源成本和效用。它是机器学习中用于分类和回归任务最基础和最广泛使用的算法之一。
- Knowledge type
- 数学理论
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-03 16:05:35
Sub-knowledge points
CART (Classification and Regression Trees)ID3 (Iterative Dichotomiser 3)C4.5Random ForestsGradient Boosting
Higher-order knowledge points
Main parameters and performance indicators
splitting criterion: metric used to select the best attribute to split the data (e.g., Gini impurity, Information Gain)max depth: maximum number of levels in the treemin samples split: minimum number of samples required to split an internal node
Open problems
Overfitting: trees can become too complex and fit noise in the training dataInstability: small changes in the data can result in a completely different tree structureBias towards dominant classes: can lead to imbalanced predictions
Related literature
ranked by community starsLightweight Machine Learning for DoS Attack Detection in Wireless Sensor Networks: An Implemented Decision Tree SystemOpen source
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1 recordsRecord title: Decision Tree.
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