Integration of machine learning algorithms and GIS-based approaches to cutaneous leishmaniasis prevalence risk mapping.
Negar ShabanpourSeyed Vahid Razavi TermehAbolghasem Sadeghi-NiarakiSoo-Mi ChoiTamer AbuhmedPublished in: Int. J. Appl. Earth Obs. Geoinformation (2022)
Keyphrases
- machine learning algorithms
- benchmark data sets
- machine learning methods
- machine learning
- learning algorithm
- predictive accuracy
- decision trees
- machine learning approaches
- learning problems
- machine learning models
- learning tasks
- random forests
- learning models
- input features
- spatial data
- standard machine learning algorithms
- supervised learning algorithms
- machine learning and data mining algorithms
- information extraction
- machine learning systems
- geographic information systems
- risk management
- data structure
- classification accuracy