COMPARISON OF THE PERFORMANCE OF GRADIENT BOOSTING, LOGISTIC REGRESSION, AND LINEAR SUPPORT VECTOR CLASSIFIER ALGORITHMS IN CLASSIFYING TRAVEL MODES BASED ON GNSS DATA

• 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.