question
active
question:how-can-we-decide-if-our-selection-of-examples-is-completeHow can we decide if our selection of examples is complete?
Central question motivating attribute exploration.
Neighborhood — ranked by edge-count
Methods (1)
method
- Interactive algorithm for discovering complete implicational knowledge by computing stem base and seeking counterexamples.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Imagines a page that reveals its hidden combinatorial potential.
- Claim about the nature of accomplishment verification.
- Einstein's assertion invoked to explain why BMR preserves accuracy while reducing complexity
- Foundational assumption for the pattern language.
- Conditional prediction that a header inflects the reading of the text block.