PersonalPredictionEngine keeps a discrete probability distribution over
candidate start dates rather than a date with a margin bolted on. Everything the
product needs falls out of that one structure: the most likely date is its mode,
the window is the narrowest span holding 80% of the mass, and a "Not yet" is the
distribution conditioned on what the user just said — which is what §13 asks for
and what a date-plus-margin design cannot express at all.
It is better, and that is a number rather than an opinion. EngineComparisonTest
scores both engines over the §51 fixtures on every build:
engine MAE mean window within +/-2 window covered
baseline 1.00 2.67 7/9 7/9
personal 0.67 4.56 9/9 9/9
COVERAGE IS THE MEASURE, NOT WIDTH
The first version of that test asserted the new windows must not be wider, and
it failed. Measuring showed why the assertion was wrong: the fixtures where the
personal engine is wider are the ones that are genuinely less certain — a
history with a suspected missing period, and one with a 45-day outlier — and the
baseline answers both with a two-day window and misses. What a window promises
is that the period starts inside it. An engine keeping that promise 7 times in 9
has a broken promise, not a tight forecast. The test now asserts coverage, with
a ceiling so "some time this month" still fails.
THREE MODELLING BUGS THE TESTS FOUND
Each was found by a test failing, not by reading the code:
- Median absolute deviation alone reads a user alternating 25 and 37 as
perfectly consistent, because half her deviations are zero. Twenty
disagreeing cycles came back High, breaking §15's rule that volume alone
must never buy High confidence. Spread is now the larger of MAD and mean
absolute deviation; robustness comes from IntervalAnalysis down-weighting
what is questionable, which is a better place for it.
- Recency weighting assumes the recent past predicts the near future. For a
variable user that is false — her latest cycle is a draw from a wide
distribution, not a signal — and weighting it equally cost three days on the
§51 variable fixture. Recency is now trusted in proportion to how much her
cycles actually agree.
- A fixed one-day floor on trend detection fired on a 42-day-cycle history
whose medians differed by a single day, turning an exact forecast into a
wrong one. One day is a real trend at 28 and rounding error at 42, so the
floor is relative to the user's own spread.
WIRED THROUGH, NOT JUST TESTED
PredictionInput carries recentAbsoluteErrors, and CycleRepository feeds the
scored errors back in. Without that the app stores every error it makes and
never reads one back — measuring accuracy rather than learning from it, with the
widening happening only in a unit test. A repository test asserts the errors
actually reach the engine.
BaselinePredictionEngine stays as the control, and both engines run the same
§51 acceptance suite, so the next engine's improvement is measurable too.
108 tests, all passing. ./gradlew check green. Verified on a device.
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