Model Performance Comparison.

BER, Kappa coefficients and Accuracy statistics calculated on the test set. Values indicated as being significantly better than the baseline (p≤0.05) are indicated in bold. Model numbers indicate the input features used; 1 indicates primary features; 2 indicates subset of features chosen by Boruta; 3 indicates all input features were used. K-NN1 is not included as the LOOcv indicated that 1 nearest neighbour gave the best performance making it the same as the baseline 1-NN model. (NB  =  Naive Bayes; RF  =  Random Forest; CT  =  Classification Tree; NN  =  Neural Network; SVM  =  Support Vector Machine; k-NN =  k-nearest neighbour).