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An Approach to Mine Data for Predicting Forest Fires Using ..:
, In:
2023 International Conference on Circuit Power and Computing Technologies (ICCPCT)
,
Prathimesh
;
Kunal
;
Shingari, Groresh
. - p. 1457-1462 , 2023
Link:
https://doi.org/10.1109/ICCPCT58313.2023.10245148
RT T1 <cTitle>2023 International Conference on Circuit Power and Computing Technologies (ICCPCT)</cTitle>: T1 <Title>An Approach to Mine Data for Predicting Forest Fires Using Support Vector Machines and Gini Index for Feature Selection</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10245148&Exemplar=1&LAN=DE A1 Prathimesh A1 Kunal A1 Shingari, Groresh A1 Sharma, Deepika YR 2023 K1 Support vector machines K1 Training K1 Machine learning algorithms K1 Vegetation mapping K1 Forestry K1 Predictive models K1 Surfaces K1 Forest Fire Prediction K1 Uncertainties K1 Machine learning K1 Data Mining K1 Gini-index SP 1457 OP 1462 LK http://dx.doi.org/https://doi.org/10.1109/ICCPCT58313.2023.10245148 DO https://doi.org/10.1109/ICCPCT58313.2023.10245148 SF ELIB - SuUB Bremen
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