ENSEMBLING OF DECISION TREES, KNN, AND LOGISTIC REGRESSION WITH SOFT-VOTING METHOD FOR WILDFIRE SUSCEPTIBILITY MAPPING

• Feature elimination algorithm that combines recursive features with voting for feature selection in forest fire susceptibility assessments. • Using the feature selection method, the primary factors can be reduced, while the evaluation criteria can be improved. • In the assessment of forest fire susceptibility, the random forest method appears to be more accurate than the support vector machine.