Based on prior knowledge, we can analyze how the feature "Frequency" relates to the task of whether the person donated blood or not.

Analysis:
- It is plausible that people who donate blood regularly would have a higher frequency of donations compared to those who do not donate. Therefore, we can expect a positive relationship between the "Frequency" feature and the target variable.
- However, it is also possible that some people have donated blood only once or a few times, while others have never donated. In such cases, the frequency may not necessarily indicate whether the person donated or not. Hence, there might be some overlap in the values of "Frequency" for both classes.

Based on this analysis, let's create a dictionary with the requested format:

```json
{
  "yes": [6.0, 9.0, 12.0, 16.0, 20.0],
  "no": [1.0, 2.0, 3.0, 4.0, 5.0]
}
```

Note: These values are just examples and represent typical frequencies for each class. The actual values will depend on the dataset being analyzed.