Prediction of forest fire risk for artillery military training using weighted support vector machine for imbalanced data

DOI10.1007/s00357-024-09467-1MaRDI QIDQ6546757

Seongil Jo, Jaeoh Kim, Ji Hyun Nam, Jongmin Mun

Publication date: 30 May 2024

Published in: Journal of Classification (Search for Journal in Brave)

zbMATH Keywords

risk predictionforest fireweighted support vector machineimbalanced data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Cites Work

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• Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets
• Cost-sensitive boosting for classification of imbalanced data
• Support-vector networks
• Measuring classifier performance: a coherent alternative to the area under the ROC curve
• Weighted Support Vector Machine Usingk-Means Clustering
• Two Modifications of CNN
• Machine Learning: ECML 2004
• Structural, Syntactic, and Statistical Pattern Recognition

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