Based on prior knowledge, the feature "Frequency" represents the total number of blood donations made by a person. To analyze its relationship with the task of whether the person donated blood or not, we can hypothesize the following:

1. Positive Relationship: People who donate blood more frequently are more likely to have donated blood in the past. So, we can expect that individuals who have donated blood in the past will have higher values of the "Frequency" feature.

2. Negative Relationship: On the other hand, individuals who haven't donated blood in the past are likely to have lower values of the "Frequency" feature.

Now, let's create a dictionary to summarize the relationship between the "Frequency" feature and the target variable:

```json
{
	"yes": [4.0, 7.0, 9.0, 10.0, 12.0],
	"no": [0.0, 1.0, 2.0, 3.0, 5.0]
}
```

In this dictionary, we have included 5 typical values for the "Frequency" feature for each target class ('yes' and 'no'). The values under the "yes" key represent values of the "Frequency" feature for individuals who have donated blood, while the values under the "no" key represent values for individuals who haven't donated blood.