Based on my prior knowledge, I can analyze the relationship between the feature "num_dependents" and the task of determining whether a person receives credit or not.

Typically, having a higher number of dependents might indicate a higher financial burden on the person. This could potentially impact their ability to manage credit obligations and increase the likelihood of them not receiving credit. On the other hand, having a lower number of dependents might indicate a lower financial burden and potentially a better chance of receiving credit.

Using this analysis, I can now create a dictionary as per the given format:

```json
{
	"yes": [0.0, 1.0, 2.0, 3.0, 4.0],
	"no": [0.0, 1.0, 2.0, 3.0, 4.0]
}
```

In this dictionary, I have included 5 typical values for the "num_dependents" feature for each target class ('yes' and 'no'). Keep in mind that these values are just examples and may vary based on the specific dataset and its characteristics.