From f2ab7f55f1942e3b992dcce60bc35f4f2436d00a Mon Sep 17 00:00:00 2001 From: kevinBell Date: Tue, 28 Jul 2026 13:05:07 -0600 Subject: [PATCH] added presentation slides --- presentation/index.html | 1209 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 1209 insertions(+) create mode 100644 presentation/index.html diff --git a/presentation/index.html b/presentation/index.html new file mode 100644 index 0000000..f468e89 --- /dev/null +++ b/presentation/index.html @@ -0,0 +1,1209 @@ + + + + + + + + Utah Vehicle Health · 10-minute deck + + + +
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0:00–0:40
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+ + + Utah Vehicle Health + Returning vehicles · next first attempt + +
+

Utah Vehicle Health

+

+ Predicting a returning vehicle's next-episode first-attempt non-pass + outcome. +

+

+ One focused prediction question — a development prototype, not a + population study or decision tool. +

+

Kevin Bell · Summer 2026 development prototype

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+ + +
+

Research question

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+ Using only information available before an inspection episode begins, + how well can a calibrated logistic regression estimate whether a + returning vehicle's next episode will have a first-attempt non-pass + outcome? +
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  • + Attempts ≤ 30 days apart form one episode — rapid + fail/retest sequences never become repeated target rows. +
    • +
  • + The target is the first attempt of a returning + vehicle's next episode. +
    • +
  • + Non-pass combines fail, reject, and abort; blanks + stay unlabeled. +
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+ + +
+

Development data

+

Complete histories for a non-representative sample

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+
+sample up to 10,000 vehicles + ↓ +retrieve their full histories + ↓ +build 30-day episodes + ↓ +44,659 eligible returning targets
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+
9,996private tokens after validation
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83,552source events
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69,588episodes
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44,659eligible targets
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+

+ Pipeline reconciliation counts — not Utah totals. + Page sampling over-represents vehicles with more records, and + feeds do not cover all 29 counties. +

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+ + +
+

Leakage-safe design

+

Every feature window ends before the target

+
+ 2010–15 context + 2016–22 train + 2023 tune + 2024 calibrate + 2025 one-time holdout + 2026 partial shadow +
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+

+ Uses (all pre-episode) +

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  • Prior outcomes, history depth, timing
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  • Vehicle age, season, public county context
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  • Previously observed make / model
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+ Excludes +

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  • Current-test diagnostics & later attempts
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  • Future records, identifiers, stations, technicians
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+ The 2025 gate was opened once after specs were + frozen — a development holdout, not a pristine future test. +

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Model comparison

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ 2025 one-time sample holdout · higher PR-AUC and lower Brier are + better · not population performance +
ModelRolePR-AUCBrier
Training prevalenceBaseline0.1230.1076
Previous episodeBaseline0.1580.1731
Logistic + PlattFinal0.2610.1011
Boosted tree + PlattBenchmark0.2380.1024
+

+ Logistic beat both baselines and the boosted-tree benchmark. We avoid + the word “accuracy,” which hides class imbalance and calibration. +

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+ + +
+

Model decision

+

Keep calibrated logistic regression

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  • + Final model: calibrated logistic regression + (C=0.03, Platt scaling). +
    • +
  • + Benchmark only: histogram gradient boosting — not a + second final model. +
    • +
  • + The tree did not improve the declared sample metrics enough to + justify its complexity. +
    • +
  • Logistic regression is easier to audit and explain.
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+ + +
+ Live dashboard demo · 2:45 +

Switch to the dashboard

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+ Follow demo_script.md. Keep the development-preview + banner in view. Show logistic as final, the tree as benchmark-only, + and that there is no vehicle-level prediction service. +

+
+ 1 · Overview + 2 · Sample cohorts + 3 · Model & benchmark + 4 · Data & methods +
+
node dashboard/server.mjs --lan → open the “Other devices” URL + /#overview
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+ + +
+

Privacy architecture

+

A deliberately narrow public boundary

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+private read-only data + → local modeling + → suppressed aggregate JSON + → allowlisted local static server + → same-network demo browser
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  • + No VINs, plates, ZIPs, stations, technician IDs, private tokens, raw + JSON, credentials, operational records, or row-level predictions. +
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  • The browser has no database connection.
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  • + The dashboard fails closed if its aggregate + contract does not validate. +
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+

Limitations

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What this sample cannot claim

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  • The page-sampled cohort is not population-representative.
    • +
  • Feeds are partial and change over time.
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  • Geography and source era are confounded.
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  • Reject / abort do not necessarily mean mechanical failure.
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  • 2025 is a one-time development holdout, not external validation.
    • +
  • + Sample associations do not support county rankings or causal + conclusions. +
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+ + +
+

Close

+

A complete, honest development prototype

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+ One precise question · a leakage-safe timeline · calibrated logistic + regression as the final model · a boosted-tree benchmark · a + privacy-reviewed static dashboard. +

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+ The value is the discipline of making only the claims the data and + release boundary can support. +

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+ Questions? +

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+ Happy to go deep on episode construction, calibration, privacy, or the + dashboard. +

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Deck controls

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+ → / SpaceNext slide + ←Previous slide + Home / EndFirst / last slide + SToggle speaker notes + FToggle fullscreen + PPrint / save as PDF (backup) + ?Show this help +
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