Based on prior knowledge, we can analyze the relationship between the feature "campaign" and the target variable "Does this client subscribe to a term deposit?". 

Typically, a higher number of contacts during a campaign may result in a higher likelihood of the client not subscribing to a term deposit. However, it is important to note that the relationship may not be linear and could be influenced by other factors.

Based on this analysis, let's create a dictionary:

```json
{
	"no": [1.0, 2.0, 3.0, 4.0, 5.0],
	"yes": [1.0, 2.0, 3.0, 4.0, 5.0]
}
```

These values represent 5 typical campaign values for each target class ('no' and 'yes'). Please note that the actual values may vary depending on the dataset and should be adjusted accordingly based on data exploration and analysis.