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Conformance checking

Conformance checking is the formal process-mining technique of comparing an event log to a reference process model and producing fitness, precision, generalisation, and simplicity scores. The output quantifies how well the model represents what's actually happening — and where the divergences concentrate.

Conformance is one of the four core process mining activities (discovery, conformance, enhancement, operational support). The fitness score (0-1) measures how much of the log the model can replay; low fitness means the model misses real behaviour. The precision score measures how much the model allows that the log never shows; low precision means the model is too permissive. The trade-off matters because models that score 1.0 on both for any non-trivial log are usually overfit. The pragmatic target: fitness above 0.85, precision above 0.7, and explanations for the major non-fitting variants.

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