Table 4.

Summary of classification metrics for the six types of models. RFC, Random Forest Classifier; LDA, Linear Discriminant Analysis; LOGIS, Logistic Regression; ANN, Artificial Neural Network; SVM, Support Vector Machine; XGBoost, Gradient Boosted Trees. The RFC was picked as it gave the best performance on three of the four classification metrics.

	Accuracy	Balanced Accuracy	Accuracy ($\pm 1$)	Spearman’s $\mathit{\rho }$
RFC	0.50	0.50	0.95	0.52
LDA	0.48	0.51	0.93	0.47
LOGIS	0.45	0.50	0.92	0.47
ANN	0.46	0.41	0.92	0.32
SVM	0.46	0.52	0.93	0.49
XGBoost	0.47	0.49	0.93	0.50