Based on my prior knowledge, the feature 'pdays' represents the number of days since the client was last contacted from a previous campaign. To analyze the relationship between this feature and the task of whether the client subscribes to a term deposit or not, I would consider the following:

1. If 'pdays' is a large positive value (e.g., 999), it could indicate that the client was not previously contacted. This might suggest that the client is more likely to subscribe to a term deposit, as they haven't been contacted recently and may be more open to exploring new financial opportunities.

2. If 'pdays' is closer to zero or a negative value, it suggests that the client was contacted more recently. This could indicate that the client is less likely to subscribe to a term deposit, as they may have already made their decision or have less interest in additional offers at the moment.

Based on these observations, here is the dictionary with typical 'pdays' values for each target class:

```json
{
	"no": [0.0, 1.0, 2.0, 3.0, 4.0],
	"yes": [999.0, 998.0, 997.0, 996.0, 995.0]
}
```

In the 'no' class, the typical 'pdays' values are closer to zero or a small positive value, indicating recent contact. In the 'yes' class, the typical 'pdays' values are large (e.g., 999), indicating no recent contact.