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

Analysis:
The number of dependents could potentially have an impact on a person's ability to receive credit. Usually, having more dependents increases a person's financial responsibilities and decreases their disposable income, which might make it harder for them to qualify for credit. 

However, it is important to note that the relationship is not necessarily linear, and other factors such as income and debt load also play a significant role in credit decisions. 

Based on this analysis, we can now create the dictionary:

```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 case, we have included the five typical num_dependents values (0.0, 1.0, 2.0, 3.0, 4.0) for both the "yes" and "no" classes. Keep in mind that these values can vary based on the specific dataset and the distribution of the num_dependents feature.