SHAP from scratch: explaining one prediction, feature by feature
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A model can tell you it approved a loan at 59%. What it won't tell you is why: which facts about the applicant earned that number, and how much each one mattered. That gap is what explainability tries to close, and SHAP is the sharpest tool we have for it. I built a small interactive version from scratch to see exactly how it works, and a few things finally clicked. The setup is a tiny loan-approval model over five features: income, credit score, debt, age, and years employed. Feed it an…
1Key Takeaways
- A model can tell you it approved a loan at 59%.
- What it won't tell you is why: which facts about the applicant earned that number, and how much each one mattered.
- That gap is what explainability tries to close, and SHAP is the sharpest tool we have for it.
- I built a small interactive version from scratch to see exactly how it works, and a few things finally clicked.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that a model can tell you it approved a loan at 59%.
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