Based on the given feature description, it appears that the SEQN feature is a unique identifier for each respondent. It is a numeric variable, but without any further information, it is not directly related to a person's age group. Therefore, it would not be possible to analyze the relationship between SEQN and the target variable of age group.

However, if we assume that there is some hidden relationship between SEQN and age group, we can create a dictionary with some example values. Please note that without additional information, these values are purely fictional and may not reflect any actual relationship between SEQN and age group.

```json
{
	"Adult": [10002.0, 20007.0, 30011.0, 40015.0, 50021.0],
	"Senior": [60034.0, 70042.0, 80055.0, 90067.0, 100079.0]
}
```

In this example, we have provided five SEQN values for each target class, "Adult" and "Senior". Again, please note that these values are completely arbitrary and have no real significance without further information on the relationship between SEQN and age group.