Based on prior knowledge, the feature "Frequency" represents the total number of blood donations made by a person. To analyze the relationship between this feature and the task of whether the person donated blood, we can consider the following:

1. Intuitively, individuals who have donated blood multiple times (higher Frequency values) are more likely to donate blood again in the future.
2. On the other hand, individuals with very low Frequency values might not have a habit of donating blood regularly and may be less likely to donate again.

Based on these assumptions, we can generate a dictionary as follows:

```json
{
  "yes": [1.0, 2.0, 3.0, 4.0, 5.0],
  "no": [0.0, 0.0, 0.0, 0.0, 0.0]
}
```

In this case, for the target class 'yes' (representing individuals who donated blood), we assume typical Frequency values to be 1.0, 2.0, 3.0, 4.0, and 5.0. This suggests that people who have donated blood at least once are more likely to donate again.

For the target class 'no' (representing individuals who did not donate blood), we assume typical Frequency values to be 0.0. These individuals have not donated blood in the past, so they are less likely to donate in the future.

Please note that the assumption of typical Frequency values depends on the specific dataset and the distribution of values within it. The provided values above are an example and may vary depending on the actual data.