一种在WEKA中使用简单CART算法进行分类的方法

N. Bhargava, Sonia Dayma, Abishek Kumar, Pramod Singh
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引用次数: 36

摘要

该决策树通常适用于数据挖掘,以产生一个基于各种输入或自变量的预测对象或其因变量值的框架。CART算法主要应用于医学、统计学等领域。对于心脏病患者来说,医生预测心脏病发作是很复杂的,因为这是一项需要经验和知识的复杂任务。论文第一部分介绍了CART算法的关联应用及其分类方法。另一部分代表了真实世界的男性患者数据集,用于进一步分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach for classification using simple CART algorithm in WEKA
This decision tree is normally applicable in data mining in order to produce a framework that predicts the value of object or its dependent variable, established on the various input or independent variable. CART algorithms are mainly used in Medical, Statistics etc. For heart disease patients it is complex for medical practitioners to predict the heart attack as it is a complex task that requires experience and knowledge. First part of paper has introduced the CART algorithm with associative applications and its classification method. Other part has represented a real world dataset of male patient taken for further analysis.
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