|
| 决策树分类算法研究 |
| Research into the Decision Tree Classification Algorithmsrule |
| |
| DOI：10.3969/j.issn.1671-5322.2005.04.007 |
| 中文关键词: 决策树 数据挖掘 信息增益 |
| 英文关键词: decision tree data-scooping information gain |
| 基金项目: |
|
| 摘要点击次数: 4978 |
| 全文下载次数: 3707 |
| 中文摘要: |
| 决策树分类算法是数据挖掘研究中的一个以样本数据集为基础的归纳学习方法,它着眼于从一组无次序、无规则的样本数据集中推理出决策树表示形式的分类规则,提取描述样本数据集的数据模型.讨论了决策树分类算法的基本原理,给出了算法的特性并通过一个实例给出了具体的使用方法. |
| 英文摘要: |
| The decision tree classification algoriellm is a inductive learning method colich is based on the data sets in data-scooping research.The methool focuseson deducing the classification rules in the form of decision tree from a group of random,irregular sample data sets,and drawing the data model which can descuibe the sample data sets.The basic principles of the method are also discassed to point out its clcaracteristics,in which the real usage is illustrcted by an exanple. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |