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Machine learning · Measurement
Averaging threw the answer away before the model ever saw it
The number my model predicts is an average, and averaging deletes what tells two shapes apart. On corrected data the recovery is small: +0.02 at worst.
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Machine learning · Measurement
There was a random number hiding inside my measurement
I reported that a descriptor loses its value when computed cheaply. The collapse was a random draw my own solver made, and the check meant to catch it passed.
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Machine learning · Measurement
The training set moves the error 390x. Nothing predicts it.
Across 231 training-set choices the worst case moved by a factor of 390. I tested nine cheap ways to pick a good one. None of them held up.
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Machine learning · Measurement
The metric was measuring my model, not the problem
A transferability score held at 0.54 across two independent budgets, then collapsed to 0.14 when I changed the model class. It was tracking the algorithm.
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Supply chain · Measurement
You cannot count the sale you did not make
Sales data records what you sold, not what people wanted. The two differ exactly on the days they matter most, and the gap teaches a forecast to shrink.
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Machine learning · Supply chain
My model scored perfect and that was the problem
A perfect held-out score measured one thing: whether the model could repeat what it had seen. Of 30 cross-family tests, 20 fell below a crude baseline.