Minor rewording about how good optuna calib results results are
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- "Compared to `scipy.optimize.minimize()`, Optuna took less time and produced a much better fit. However, it's still far from perfect -- more iterations, and calibrating more parameters beyond just these two, would still be required before the model could be considered \"calibrated\".\n",
+ "Compared to `scipy.optimize.minimize()`, Optuna took less time and produced a better fit. Specifically, the mismatch obtained with Optuna is almost half the smallest mismatch achieved with `scipy.optimize`. However, Optuna's results are still far from perfect -- running calibration runs, or more iterations, and calibrating more parameters beyond just these two, would still be required before the model could be considered \"calibrated\".\n",
"\n",
"Sometimes you want to calibrate a parameter that isn't a built-in parameter -- for example, part of an intervention. You can do this using the `custom_fn` keyword argument. In this example, we calibrate the test probability by modifying the `test_prob` intervention directly."
]
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- "version": "3.9.7"
+ "version": "3.9.10"
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