Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data.
Biobele J. BrownAlexander A. PrzybylskiPetru ManescuFabio CaccioliGbeminiyi OyinloyeMuna ElmiMichael J. ShawVijay PawarRemy ClaveauJohn Shawe-TaylorMandayam A. SrinivasanNathaniel K. AfolabiAdebola E. OrimadegunWasiu A. AjetunmobiFrancis AkinkunmiOlayinka KowobariKikelomo OsinusiFelix O. AkinbamiSamuel OmokhodionWuraola A. ShokunbiIkeoluwa LagunjuOlugbemiro SodeindeDelmiro Fernandez-ReyesPublished in: CoRR (2019)
Keyphrases
- collected data
- machine learning approaches
- data driven
- densely populated
- data collection
- machine learning methods
- collecting data
- machine learning
- machine learning algorithms
- prediction accuracy
- machine learning models
- data mining methods
- prediction model
- prediction error
- prediction algorithm
- urban areas
- data sources
- data sets
- decision support
- database
- data management
- years ago
- urban planning
- information technology
- question classification
- data mining