决策树(Decision Tree)是数据挖掘中一种最基本的分类与回归方法,与其他的算法相比,决策树的原理浅显易懂,计算复杂度较小,而且输出结果易于理解,因此在实际中有着广泛的应用。 一个简单的决策树示例(图片来源:机器学习 (豆瓣)): 决策树可以被认为是一种'if-then'规则的集合。它由节点和有向边组成,内部节点代表...
Pruning is a general technique to guard against overfitting and it can be applied to structures other than trees like decision rules. A decision tree is pruned to get (perhaps) a tree that generalize better to independent test data. (We may get a d
We show that the decision tree representation and the knowledge rules repre-sentation for data mining are semantically equivalent. Quinlan's production rule generators use attribute removal functions that are more powerful than ID3. The HCC-algorithm uses both attribute removal and concept tree ...
Multi-Attribute Decision Trees and Decision Rules (2006). Multi-attribute decision trees and decision rules. in Data Mining and Knowledge Discovery Approaches Based on Rule Induction Tech- niques, p. 327... JY Lee,S Olafsson - Springer US 被引量: 21发表: 2006年 Decision tree-based data min...
Second, the decision tree uses the target variable to determine how each input should be partitioned. In the end, the decision tree breaks the data into segments, defined by the splitting rules at each step. Taken together, the rules for all the segments form the decision tree model. ...
CHAPTER 8 Decision Tree Algorithms Decision trees provide a means to obtain product-specific forecasting models in the form of rules that are easy to implement. These rules have an if-then … - Selection from Data Mining Models [Book]
Decision tree (decision tree), also known as decision tree is a kind of information theory-based, decision tree data structure based on this classification algorithm. Categorized the decision tree in the field of data mining has been studied for many years, and had a lot of algorithms, such ...
Data mining methods are widely used across many disciplines to identify patterns, rules, or associations among huge volumes of data. While in the past mostly black box methods, such as neural nets and support vector machines, have been heavily used for the prediction of pattern, classes, or ev...
This paper describes an approach to generating the rules for an agent from a large training set. A set of decision trees are built in parallel on tractable size training data sets which are a subset of the original data. Each learned decision tree will be reduced to a set of rules, ...
12.1.1 Decision Tree Rules Introduces Decision Tree rules. Oracle Data Mining supports several algorithms that provide rules. In addition to decision trees, clustering algorithms provide rules that describe the conditions shared by the members of a cluster, and association rules provide rules that de...