Tested, real model use on real data: safe, certifiable, repeatable and auditable predictive AI — every number shown, every limitation stated.
A real fraud-classification experiment scored 99.9% accuracy on 28,306 held-out transactions, yet missed 14 of 50 frauds. Here is why accuracy alone misleads on imbalanced data.
An accuracy figure is a claim. Certification is the evidence behind it: how we check that a model earned its score honestly, and why we would rather say 'not assessed' than guess.
Held-out evaluation tests a predictive model on data it never saw during training. Here is how it works, why in-sample accuracy flatters, and a worked example on 28,306 transactions.
Predictive models turn rows of structured data into a class or a number and can be measured on held-out data. Generative models turn prompts into new text. Here is when each one fits.
Yes — if the CSV has one row per case, a target column with known past outcomes, and enough examples. Here is what your file needs, what to remove, and how the process works.