Based on the given feature description, the feature SEQN is the respondent sequence number. Since there is no additional information about the feature, we can assume that it does not have a direct relationship with the target variable, which is the person's age group.

Therefore, it is unlikely that we can analyze the feature SEQN to predict the person's age group accurately. However, we can still provide an example dictionary considering random values for the SEQN feature for the target classes 'Adult' and 'Senior':

```json
{
	"Adult": [10001.0, 10002.0, 10003.0, 10004.0, 10005.0],
	"Senior": [20001.0, 20002.0, 20003.0, 20004.0, 20005.0]
}
```

Please note that these values are just placeholders and do not have any real relationship to the feature SEQN or the target variable.