Based on prior knowledge, we can analyze the relationship between the feature installment_commitment and the task of whether a person receives a credit or not.

Analyzing the data, we can assume that higher installment_commitment values may indicate a higher risk of defaulting on credit payments. Therefore, it is possible that lower values of installment_commitment would be more common for those who receive credit, while higher values would be more common for those who do not receive credit.

Here is the dictionary with the specific details:

```json
{
	"yes": [10.0, 12.0, 15.0, 8.0, 9.0],
	"no": [20.0, 25.0, 18.0, 22.0, 30.0]
}
```

In this example, we have included typical values for installment_commitment for each target class ('yes' and 'no'). The values provided are just an example and may not accurately represent the actual data.