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ATM model for a DCA experiment
Optimization and inter-model variance: Use a fourteenth shipping model with the nine new features. Randomly subsample to keep only 50% of the training DBs (although we still use all validation DBs). https://ml.azure.com/runs/classification_1661795142_49c13ac0?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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version: 0.0.97+2022-08-29-10h45m36s.gifted-cumin-f9snbq1x.7f53df4cba996e2e96c9f6ce15a78cc73e41f06c6b8a073d12d17b3332920f88
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javascript/ql/experimental/adaptivethreatmodeling/src/qlpack.yml

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dsp-testing/javascript-experimental-atm-model: 0.0.96+2022-08-29-10h45m23s.red-vinegar-xxr4hgfk.930e539f12fb5a1e27e840c8a276df29e81347fdd429690e30a00eabf1be4369
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dsp-testing/javascript-experimental-atm-model: 0.0.97+2022-08-29-10h45m36s.gifted-cumin-f9snbq1x.7f53df4cba996e2e96c9f6ce15a78cc73e41f06c6b8a073d12d17b3332920f88

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