Comparing the performance of two machine learning models, including (i) random forests and (ii) support vector machine, on four performance metrics. Both models were trained to classify the input vector as either normal or cancer DNA when the input vector was composed of colour intensities extracted from 6 wells of the unknown solution and 18 wells of the reference one (24 dimensional feature vector).

Model	Performance
	Accuracy	Precision	Recall	F1-score
Random forests	0.90	0.93	0.90	0.92
Support vector machine	0.90	0.97	0.90	0.93