Measuring Data Processing Effectiveness: Defining Insight and Compression Efficiency
By
mbuda
Hard to chew. Probably not worth the jaw work.
Summary
The article discusses methods for measuring how much data a person can effectively process or understand, focusing on defining 'insight' as a measurable reduction in uncertainty that improves decision quality or predictive accuracy. It proposes practical definitions of insight including testable hypotheses, model parameter adjustments, and structural relationships that reduce entropy. The author suggests measuring compression efficiency as (uncertainty reduced) / (data processed) and considers breadth as dimensional coverage of independent variables or graph regions.
Key quotes
· 4 pulledBy 'insight' I mean a measurable reduction in uncertainty that improves decision quality or predictive accuracy.
An insight could be defined as: • A hypothesis generated and testable from the dataset • A model parameter adjustment that increases predictive performance • A structural relationship discovered that reduces entropy in the system representation
Compression efficiency would be something like: (uncertainty reduced) / (data processed)
Breadth is interesting — I'd treat it as dimensional coverage: how many independent variables or graph regions are meaningfully covered
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