After analyzing the relationship between the feature RIAGENDR (Respondent's Gender) and the task of predicting the age group, it can be inferred that the feature has a potential influence on the target variable. Typically, different age groups may have different gender distributions, which can be useful for predicting the age group of a person.

To create the dictionary, we will assign the target classes 'Adult' and 'Senior' to the appropriate ranges of values for RIAGENDR:
- For 'Adult', we will consider values of RIAGENDR from 1.0 to 1.5, which represent males.
- For 'Senior', we will consider values of RIAGENDR from 1.5 to 2.0, which represent females.

Based on these ranges, the following dictionary can be generated:

```json
{
	"Adult": [1.0, 1.1, 1.2, 1.3, 1.4],
	"Senior": [1.5, 1.6, 1.7, 1.8, 1.9]
}
```

Please note that the values assigned to the lists are just examples and can be adjusted based on the specific dataset being analyzed.