基于单纯形的社会蜘蛛优化方法改进医疗数据分析

Computer Science & Engineering: An International Journal Pub Date : 2022-02-28 DOI:10.5121/cseij.2022.12111

Monalisa Nayak, Soumya Das, U. Bhanja, Manas Ranjan Senapati

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引用次数: 0

摘要

准确可靠的预测是预防疾病传播的唯一途径。许多机器学习模型已经被开发用于预测大规模的医疗数据集。本文采用基于单纯形的Social Spider Optimization方法对心脏病、超声心动图和肝炎三种类型的医疗数据集进行分类。利用均方根误差(RMSE)和时间来获得模型的性能。

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Simplex based Social Spider Optimization Method for Improving Medical Data Analysis

Accurate and reliable prediction is the only way to prevent the disease transmission. Many machine learning models have been developed for prediction of large scale medical datasets. In this paper, Simplex based Social Spider Optimization method is used for classification of three types of medical datasets like heart disease, echocardiogram and hepatitis. The performance of the model is obtained by using Root Mean Square Error (RMSE) and time.

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Computer Science & Engineering: An International Journal

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