Data mining research based on decision tree algorithm taking the patient's condition data of respiratory department in hospital as an example

J. Tang, Wenjuan Zhao
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Abstract

This paper proposes a data mining method for information systems based on decision tree algorithm, establishes a more effective data mining model, and improves the accuracy and efficiency of hospital data mining. Based on the C4.5 decision tree algorithm, the model adds methods such as cosine similarity judgment, which reduces resource consumption, greatly improves the accuracy, and takes the clinical diagnosis data of 5 common diseases in respiratory medicine as a sample and obtains more efficient and accurate data results through simulation testing.
基于决策树算法的数据挖掘研究,以医院呼吸科患者病情数据为例
本文提出了一种基于决策树算法的信息系统数据挖掘方法,建立了更有效的数据挖掘模型,提高了医院数据挖掘的准确性和效率。该模型在C4.5决策树算法的基础上,增加了余弦相似度判断等方法,减少了资源消耗,大大提高了准确率,并以呼吸医学5种常见疾病的临床诊断数据为样本,通过仿真测试得到了更加高效准确的数据结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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