For a more realistic example, this phenomenon of a more accurate model being worse is a common issue in database query optimization.
When a user runs a SQL query, the optimizer uses statistics about the data to estimate the cost of many different ways to execute the query, then picks the plan with the cheapest estimate.
When the optimizer misestimates the cost and chooses a bad plan, the typical solution is to add more detailed statistics about the data. But occasionally adding more statistics can cause the optimizer to choose a plan that’s actually worse.
For a more realistic example, this phenomenon of a more accurate model being worse is a common issue in database query optimization.
When a user runs a SQL query, the optimizer uses statistics about the data to estimate the cost of many different ways to execute the query, then picks the plan with the cheapest estimate.
When the optimizer misestimates the cost and chooses a bad plan, the typical solution is to add more detailed statistics about the data. But occasionally adding more statistics can cause the optimizer to choose a plan that’s actually worse.