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End-to-end Log Anomaly system for the Nokia Log AD Challenge. 🏆 Winners

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Prakhar0409/Log-Anomaly-Detection

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preprocess.py -> preprocess the GOLDEN log files

auto_test.py -> preprocess the TEST log files

parselog.py -> parses the log into template files

[NEW]step4.py -> compares the test templates to the train templates and generates folder structure to allow learning [OLD]tester.py -> compares the test templates to the train templates

To learn stuff

parselog_and_save.py -> parses the log into template files and save elarnt model to models/ folder

python3 parselog_and_save.py 'test/inputdir/' 'test/out1'

learn_more.py -> Use the models from parselog_and_save.py and folder structure from step4.py to make model learn more

python3 learn_more.py 'test/newtemplates/' 'test/out1/' 'test/out2'

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