Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature
MTMT : 32770489
Date : 2022
Journal title : Frontiers In Environmental Science
Journal volume : 10
Pages : 12.jan
Document type : folyóiratcikk
Subject : dew point temperature, random forest, multivariate adaptive regression splines, machine learning, bigdata, artificial intelligence, Természettudományok, Környezettudományok
Abstract :
Results: As a result, the GSVMA hybrid method performs better than other methods. This proposed method has the highest accuracy of 89.45% through a 10-fold crossvalidation technique with 31 selected features on the Z-Alizadeh Sani dataset.