Based on the given description, the feature SEQN represents the Respondent Sequence Number. To determine the appropriate ranges of values for different age groups, we can assume that individuals are grouped into 'Adult' and 'Senior' based on common age categories. 

Since there is no specific age information provided, we will make some assumptions regarding age ranges:
- Adults: Typically ranging from 18 to 64 years old.
- Seniors: Typically aged 65 years and above.

Using these assumptions, we can analyze how the feature SEQN relates to the 'Adult' and 'Senior' age groups. However, it's important to note that without more details or additional features, the SEQN itself may not be informative in predicting an individual's age group accurately.

Based on this analysis, we can create a dictionary with typical SEQN values for each target class:
```json
{
	"Adult": [100001.0, 100020.0, 100043.0, 100065.0, 100088.0],
	"Senior": [200001.0, 200020.0, 200045.0, 200070.0, 200092.0]
}
```

Please note that the SEQN values provided above are just placeholders. In a real scenario, you would need to analyze the actual data to determine the appropriate SEQN values for each target class.