Based on prior knowledge, we can analyze the relationship between the feature "pdays" and the task of whether the client subscribes to a term deposit.

Typically, a client will have a "pdays" value of -1 if they were not previously contacted during the campaign. A value of 0 indicates that the client was contacted on the previous day. Generally, a longer time since the last contact may imply a decreased chance of the client subscribing to a term deposit.

To analyze the relationship in more detail, we can examine typical values for "pdays" for each target class ('no', 'yes'):

For clients who did not subscribe to a term deposit ('no'):
- Typical pdays values: [-1, -1, -1, -1, -1]
 
For clients who subscribed to a term deposit ('yes'):
- Typical pdays values: [300, 400, 500, 600, -1]

Based on this analysis, we can create a dictionary with the specified format:

```json
{
	"no": [-1.0, -1.0, -1.0, -1.0, -1.0],
	"yes": [300.0, 400.0, 500.0, 600.0, -1.0]
}
```

This dictionary represents the typical "pdays" values for each target class ('no', 'yes').