Based on the feature description, the feature "RIAGENDR" represents the respondent's gender, where the value 1 represents Male and the value 2 represents Female. To analyze the relationship between this feature and the task of predicting the age group, we can consider the typical gender distributions within different age groups.

Typically, seniors refer to individuals who are 65 years old or older. For this analysis, we will assume that this age threshold is used to classify someone as a senior.

Here is the dictionary with the requested information:

```json
{
    "Adult": [1.0, 1.0, 2.0, 2.0, 2.0],
    "Senior": [1.0, 1.0, 2.0, 2.0, 2.0]
}
```

In this dictionary, the key "Adult" represents the target class for non-senior individuals, and the key "Senior" represents the target class for senior individuals. The values under each key represent the possible values of the feature "RIAGENDR" (respondent's gender) for each target class. The values are represented as floats in lists.

Please note that the specific values provided in the dictionary are just placeholders, and you would need to replace them with the actual values from your dataset.