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Table E.2.

Training machine learning methods on image data of Fornax and evaluating it on Virgo image data.

averaged per galaxy average over all sources

Method TPR FPR FDR AUC ROC TPR FPR FDR AUC ROC # TPs # FPs
Nearest Neighbour 0.81 0.04 0.31 0.86 0.04 0.15 10613 1926
12 Nearest Neighbours 0.80 0.04 0.31 0.96 0.86 0.04 0.15 0.97 10676 1815
Random Forest 0.77 0.04 0.32 0.95 0.85 0.04 0.15 0.97 10468 1823

Convolutional Neural Network (CNN) 0.90 0.03 0.20 0.99 0.93 0.02 0.09 0.99 11560 1194
CNN + Nearest Neighbour 0.84 0.03 0.20 0.88 0.02 0.09 10920 1132
CNN + 12 Nearest Neighbours 0.86 0.02 0.15 0.98 0.91 0.02 0.06 0.99 11239 770

Notes. The Virgo data contains in total 62581 sources (we excluded sources from VCC538 as it contained a lot of false positives from a background galaxy) with 12385 catalogued GCs. Results are given for a decision threshold of 0.5. Similar to Table 5.

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