Based on my prior knowledge, the "checking_status" feature represents the status of the existing checking account of a person. This feature is a categorical variable with four categories: '<0', '0<=X<200', 'no checking', and '>=200'. 

To analyze the relationship between the "checking_status" feature and the task of whether the person receives a credit or not, we can examine the distribution of "checking_status" for each target class.

Here is the analysis:

For target class "yes" (person receives a credit):
- Possible values of the "checking_status" feature for this class: ['<0', '0<=X<200', 'no checking', '>=200']

For target class "no" (person does not receive a credit):
- Possible values of the "checking_status" feature for this class: ['<0', '0<=X<200', 'no checking']

Based on the analysis, we can create the following dictionary:

```json
{
	"yes": ["<0", "0<=X<200", "no checking", ">=200"],
	"no": ["<0", "0<=X<200", "no checking"]
}
```

This dictionary provides the possible values of the "checking_status" feature for each target class.