Based on my prior knowledge, I can analyze the relationship between the feature duration (last contact duration) and the task of whether the client subscribes to a term deposit.

To analyze the relationship, I would consider the following:

1. Generally, a longer duration of the last contact might indicate a higher level of engagement or interest from the client. This could potentially increase the likelihood of the client subscribing to a term deposit.

2. However, there might be cases where a shorter duration of the last contact results in a positive outcome for the task if the conversation was concise and effective.

Based on this analysis, I would generate a dictionary with typical duration values for each target class:

```json
{
	"no": [100.0, 200.0, 300.0, 400.0, 500.0],
	"yes": [300.0, 400.0, 500.0, 600.0, 700.0]
}
```

Note: These values are not based on any specific dataset, but rather on general insights about the relationship between duration and subscription to a term deposit.