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ATM model for a DCA experiment
Optimization and inter-model variance: Use a twelfth shipping model with the nine new features. Randomly subsample to keep only 25% of the training DBs (although we still use all validation DBs). https://ml.azure.com/runs/classification_1661795071_311d6468?wsid=/subscriptions/91095667-e119-4555-acea-1826488492f0/resourcegroups/ATM-CodeML/workspaces/ATM-Workspace&tid=398a6654-997b-47e9-b12b-9515b896b4de
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dsp-testing/javascript-experimental-atm-model:
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javascript/ql/experimental/adaptivethreatmodeling/src/qlpack.yml

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dsp-testing/javascript-experimental-atm-model: 0.0.95+2022-08-29-10h34m48s.nifty-knee-zhkm8d4b.0f7165ab2368fe2b4334e099ec26cf1f619cb909c4569c0a90876a7ceb276a75
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dsp-testing/javascript-experimental-atm-model: 0.0.95+2022-08-29-10h44m25s.epic-yam-qfvpz20x.6589b58028ca702f4171565ba9983f84a83ad1d3ceeaa73695333a2da25b31f2

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