Why Powerful ML Is Deceptively Easy, Part 2

Machine learning models for real estate capital gains or rent forecasting often appear deceptively accurate when evaluation ignores spatial dependence, repeated assets, and uneven regional coverage. Random train-test splits allow nearby observations to leak between sets, creating overly optimistic error estimates that fail to test true generalization beyond familiar neighborhoods.