Analysis:

The feature "RIAGENDR" represents the respondent's gender. According to the given information, the values 1 and 2 represent Male and Female respectively. To analyze the relationship between the feature and the task of predicting age group, we can look at the distribution of gender within the different age groups.

Typically, in societies, the senior age group consists of individuals who are older than a certain threshold, such as 60 or 65 years old. Therefore, based on this prior knowledge, we can assume that individuals who fall into the senior age group will have higher values for "RIAGENDR" (Female, represented by 2) as compared to the adult age group.

However, it is important to note that this assumption is based on general societal trends and may vary depending on the specific dataset or population being analyzed.

Dictionary:

```json
{
	"Adult": [1.0, 1.0, 1.0, 1.0, 2.0],
	"Senior": [2.0, 2.0, 2.0, 2.0, 2.0]
}
```
In the above dictionary, the keys represent the target classes, 'Adult' and 'Senior'. The values associated with each key represent the possible values of the feature "RIAGENDR" that are typically found for each target class. As the target class 'Adult' is assumed to have a higher proportion of males, the values for 'Adult' are mostly 1.0 (representing Male). Similarly, as the target class 'Senior' is assumed to have a higher proportion of females, the values for 'Senior' are mostly 2.0 (representing Female).