Based on prior knowledge, the feature "residence_since" can be analyzed in relation to the task of determining whether a person receives credit or not. 

To analyze this relationship, we can look at common patterns or trends that might indicate whether a person receiving credit or not. Here are the typical residence_since values for each target class:

- For individuals who receive credit ("yes"):
  - 4.0 years
  - 3.0 years
  - 2.0 years
  - 5.0 years
  - 6.0 years

- For individuals who do not receive credit ("no"):
  - 1.0 year
  - 7.0 years
  - 8.0 years
  - 10.0 years
  - 15.0 years

Based on this analysis, we can create a dictionary with the feature values for the target classes:

```json
{
    "yes": [4.0, 3.0, 2.0, 5.0, 6.0],
    "no": [1.0, 7.0, 8.0, 10.0, 15.0]
}
```