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Hunt, K.J. (1992) Induction of Decision Trees for Rule-Based Modelling and Control. Proceedings of the 1992 IEEE International Symposium on Intelligent Control, Glasgow, 11-13 August 1992, 306-311.
http://dx.doi.org/10.1109/ISIC.1992.225108

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  • 标题: MATLAB编译生成AUTOLISP代码实现可变ID3基因分型决策树分类图的绘制Generating AUTOLISP Code to Achieve the Diagram Drawing of Variable ID3 Genotyping Decision Tree Classifier by Compiling of MATLAB

    作者: 李宏彬, 赫光中

    关键字: ID3决策树, 图的绘制, MATLAB, AUTOLISPID3 Decision Tree Classifier, Drawing Diagram, MATLAB, AUTOLISP

    期刊名称: 《Computer Science and Application》, Vol.6 No.6, 2016-06-28

    摘要: 决策树分类器,是一种基于实例的分类算法,广泛被应用于人工智能领域。ID3算法是最为经典的决策树建树算法,它通过递归和逐次挑选信息量最多的属性来构造决策树。决策树的结构有时非常庞大和复杂,而决策树分类图看起来非常直观,并且可以从建树的原始数据集中挖掘出一些关键的信息,因此决策树图的绘制是非常必要的。本研究从分子生物学领域中的基因分型决策树绘制为实例,浅谈如何使用MALAB语言编译生成AUTOLISP代码,从而实现可变ID3基因分型决策树分类图的绘制。 Decision tree classifier is a kind of classification algorithm based on examples, which is widely used in the field of artificial intelligence. ID3 algorithm is the most classical decision tree construction algorithm. It constructs a decision tree by recursion, and the selection of the attribute which contains the most amount of information. The structure of one decision tree classifier sometimes is very large and complex, decision tree classification diagram is very intuitive, and some key information can be mined from the original data set, so the decision tree diagram drawing is very necessary. This study give us an example on genotyping decision tree drawing classifier in the domain of molecular biology, and talk about how to use the MALAB language compiler to generate AUTOLISP code, so as to achieve diagram drawing of a variable ID3 genotyping decision tree classifier.

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