Prediction of forest fire occurrences in peatlands - unbalanced - Data using hybrid ADASYN-machine learning method

The literature review found that only a few studies in Indonesia have been applied to modeling peatlands fire occurrences. In our previous studies, various machine learning classification approaches are applied to predict forest fire occurrence in the peatlands area. Our previous empirical study fou...

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Hauptverfasser:	Rosadi, Dedi, Arisanty, Deasy, Andriyani, Widyastuti
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptive sampling Classification Datasets Forest fires Literature reviews Machine learning Peatlands
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creator	Rosadi, Dedi Arisanty, Deasy Andriyani, Widyastuti
description	The literature review found that only a few studies in Indonesia have been applied to modeling peatlands fire occurrences. In our previous studies, various machine learning classification approaches are applied to predict forest fire occurrence in the peatlands area. Our previous empirical study found that the datasets of fire hotspot areas, especially for data from the South Kalimantan area, need to be more balanced. In this paper, we consider ADAptive SYNthetic (ADASYN) method for the sampling approach to balance the datasets. We found that by balancing the data, the performance of the classification method can improve about 2-4%.
doi_str_mv	10.1063/5.0204719
format	Conference Proceeding
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subjects	Adaptive sampling Classification Datasets Forest fires Literature reviews Machine learning Peatlands
title	Prediction of forest fire occurrences in peatlands - unbalanced - Data using hybrid ADASYN-machine learning method
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