The Classification Performance using Support Vector Machine for Endemic Dengue Cases

The Classification Performance using Support Vector Machine for Endemic Dengue Cases

Dengue fever (DF) and the potentially fatal dengue haemorrhagic fever (DHF) are continue to be a crucial public health concern in Malaysia. This paper proposes a prediction model that incorporates Support Vector Machine (SVM) in predicting future dengue outbreak. Datasets used in the undertaken stud...

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Bibliographic Details
Main Authors: Abd Razak, N.F (Author), Ismail, N.A (Author), Mahmud, M. (Author), Mohd Sobri, N. (Author), Nordin, N.I (Author), Wan Yaacob W.F (Author), Zulkifli, S.N (Author)
Format: Article
Language:English
Published: Institute of Physics Publishing, 2020
Subjects:
Classification performance
Dengue haemorrhagic fevers
Forecasting
Functions
Gaussian radial basis functions
Polynomial functions
Potentially fatal
Prediction accuracy
Prediction performance
Radial basis function networks
RBF kernel function
Support vector machines
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