Inspiration: “Using the human language as a source of inspiration, fuzzy systems (FS) model linguistic imprecision and solve uncertain problems based on a generalization of traditional logic, which enables us to perform approximate reasoning.” [1]
Full disclosure —I’m biased towards Fuzzy Systems, so I’ll try to stick to the facts. There are many ways to explain this topic, but I like to start with Fuzzy Sets. Traditional set theory forces elements to belong to one set or another. For example, a horse belongs to the set of mammals, and a frog belongs to the set amphibians.
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The idea is part of this collection:
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Understanding machine learning models
Improving data analysis and decision-making
How Google uses logic in machine learning
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