Assessing machine learning methods in predicting dengue incidence using climatic factors in Region IV-A (CALABARZON), Philippines

Assessing machine learning methods in predicting dengue incidence using climatic factors in Region IV-A (CALABARZON), Philippines

Region IV-A or CALABARZON in the Philippines records a high number of dengue cases annually. Several studies worldwide have used machine learning techniques using climatic factors to forecast dengue outbreaks. In this study, the performance of six machine learning models namely (a) Random Forest, (b...

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Bibliographic Details
Main Authors: Castro, Ian Kevin G., Elquiero, Nikki Elisha M., Fradejas, Jericho D.
Format: text
Language:English
Published: Animo Repository 2023
Subjects:
Dengue > Philippines
Machine learning
Biology
Online Access:https://animorepository.dlsu.edu.ph/etdb_bio/27
https://animorepository.dlsu.edu.ph/context/etdb_bio/article/1028/viewcontent/2023_Castro_Elquiero_Fradejas_Assessing_machine_learning_methods_in_predicting_dengue_incidence_Full_text.pdf
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Institution: De La Salle University
Language: English

Internet

https://animorepository.dlsu.edu.ph/etdb_bio/27
https://animorepository.dlsu.edu.ph/context/etdb_bio/article/1028/viewcontent/2023_Castro_Elquiero_Fradejas_Assessing_machine_learning_methods_in_predicting_dengue_incidence_Full_text.pdf

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