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Table 4.

Classifying GCs from the combined image data sets of Virgo and Fornax.

Method TPR FPR FDR AUC ROC
Nearest Neighbour 0.842±0.005 0.033±0.002 0.122±0.006
12 Nearest Neighbours 0.847±0.008 0.023±0.001 0.088±0.004 0.975±0.002
Random Forest 0.838±0.005 0.026±0.001 0.100±0.005 0.981±0.001

Convolutional Neural Network (CNN) 0.929±0.015 0.019±0.003 0.068±0.011 0.994±0.001
CNN + Nearest Neighbour 0.912±0.006 0.026±0.001 0.094±0.004
CNN + 12 Nearest Neighbours 0.927±0.007 0.017±0.001 0.061±0.004 0.990±0.001

Notes. The reported results are averages over ten random splits (train, validation and test). Uncertainties are given as standard deviations and the used decision threshold is 0.5.

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