利用 Opt_Recurr 特征选择算法建立用于登革热预测的新型混合 SDR 模型

Q4 Mathematics
Dr. S. Nagasundaram
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引用次数: 0

摘要

登革热是一种病媒传染的疾病,有时会致命。从数据集中剔除无关和冗余特征的过程有助于选择最佳特征。本研究建议使用 Opt_Recur 算法从登革热数据集中选择最佳特征,这是一种混合 SDR 模型,与支持向量机 (SVM)、决策树 (DT) 和随机森林 (RF) 等传统分类器相比,该模型的预测准确率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Hybrid SDR Model for Dengue Prediction using Opt_Recurr Feature Selection Algorithm
Dengue is a vector borne disease , which can be fatal at times . Early detection dengue of dengue is vital as no  vaccines have been developed for dengue yet..The process of eliminating irrelevant and  redundant  features from the data set  facilitates the optimal features selection . This study is proposed to select the Optimal features by using Opt_Recur algorithm  from the Dengue  dataset  , a hybrid SDR model which makes prediction with better accuracy when compared to the conventional classifiers  like the  Support Vector Machine (SVM), Decision Tree(DT) and the Random Forest (RF) classifiers.
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CiteScore
0.30
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