Based on prior knowledge, the installment_commitment feature can be analyzed by considering two main aspects:

1. If the installment_commitment rate is high, it indicates that a larger portion of the person's disposable income is allocated towards installment payments. This could potentially imply that the person may struggle to make payments on time and may have a higher risk of defaulting on a credit.

2. If the installment_commitment rate is low, it suggests that a smaller portion of the person's disposable income is allocated towards installment payments. This indicates that the person may have a lower risk of defaulting on a credit.

Based on this analysis, we can generate a dictionary with typical values of the installment_commitment feature for each target class ('yes' and 'no').

```json
{
	"yes": [4.5, 5.7, 6.2, 7.1, 7.5],
	"no": [2.1, 3.4, 3.8, 4.2, 4.9]
}
```

Please note that the actual ranges of installment_commitment values for each target class may vary depending on the specific dataset and its characteristics.