Table 2.

AOO identification accuracies. Column one outlines the data distributions and column two outlines the grouping of the identification method as distance-based (DBI) or machine-based (MBI). Column three indicates if the 74 features were included in the order of the greatest to least important SVM weights or RF importance. Column four designates the most efficient identification method according to the least amount of features in column five, and its respective accuracy in column six. The asterisks in Trial 1 indicate the inability for RF and SVM to reach greater than 80% accuracy with less than all 74 features.

Distribution	Method Group	AOO Order	Method	# Features	Accuracy (%)
70/30	DBI	SVM Weights	ED Rank 10	3	81.05
	DBI	RF Importance	ED Rank 10	3	85.39
	MBI	SVM Weights	RF	10	80.82
	MBI	RF Importance	SVM	6	85.39
Day 1	DBI	SVM Weights	CS Rank 10	37	81.21
	DBI	RF Importance	ED Rank 10	24	84.64
	MBI	SVM Weights	SVM	29	80.93
	MBI	RF Importance	SVM	22	81.07
Trial 1	DBI	SVM Weights	ED Rank 10	27	81.05
	DBI	RF Importance	ED Rank 10	32	81.69
	MBI*	N/A*	RF*	* 74	* 70.66
	MBI*	N/A*	SVM*	* 74	* 65.94