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Table 3 Comparison of geometric semantic genetic programming (GS-GP) with other machine learning methods. A P-value less than α = 0.014 indicates that GS-GP is superior. LIN stands for linear regression, RBF for radial basis functions, ISO for isotonic regression, SVM-2 for support vector machines with polynomial kernel of degree 2, NN for neural networks, and RF for random forests.

From: Predicting Burned Areas of Forest Fires: an Artificial Intelligence Approach

   LIN RBF ISO SVM-2 NN RF
GS-GP TRAIN <0.001 <0.001 <0.001 0.13 <0.001 0.07
TEST <0.001 <0.001 <0.001 0.06 <0.001 0.004