Based on my prior knowledge, I can analyze the relationship between the feature 'pdays' and the task of determining whether the client subscribes to a term deposit or not.

Typically, the feature 'pdays' represents the number of days that have passed since the client was last contacted from a previous campaign. Here, if a client has never been contacted before, the feature value will be set to 999, indicating that the client has not been contacted yet. For clients who have been previously contacted, the lower the value, the lower the number of days since the last contact.

To analyze the relationship between 'pdays' and the task, I will consider typical pdays values for each target class ('no' and 'yes').

For clients who do not subscribe to a term deposit ('no'), typical pdays values could be:
- 999 (indicating no previous contact)
- 0 (indicating the client was contacted today or within the last day)
- 1 (indicating the client was contacted within the last week)
- 7 (indicating the client was contacted within the last month)
- 30 (indicating the client was contacted within the last 3 months)

For clients who subscribe to a term deposit ('yes'), typical pdays values could be:
- 999 (indicating no previous contact)
- 1 (indicating the client was contacted within the last week)
- 15 (indicating the client was contacted within the last 2 weeks)
- 60 (indicating the client was contacted within the last 2 months)
- 180 (indicating the client was contacted within the last 6 months)

Based on this analysis, we can generate the following dictionary:

```json
{
	"no": [999.0, 0.0, 1.0, 7.0, 30.0],
	"yes": [999.0, 1.0, 15.0, 60.0, 180.0]
}
```