Based on the given feature description, we can assume that the feature "Frequency" represents the total number of times a person has donated blood.

To analyze the relationship between the feature "Frequency" and the task "Did the person donate blood? Yes or no?", we can make some assumptions based on prior knowledge. Generally, individuals who donate blood more frequently are more likely to continue donating in the future. Therefore, we can expect a positive relationship between the feature "Frequency" and the target variable "Did the person donate blood?". 

Here's an analysis of the relationship between the feature and target variable:

- For individuals who donated blood (target class: "yes"):
   - Typical Frequency values may include: 1, 3, 5, 7, 10
   
- For individuals who did not donate blood (target class: "no"):
   - Typical Frequency values may include: 0, 2, 4, 6, 8

Based on this analysis, we can create the following dictionary:

```json
{
	"yes": [1.0, 3.0, 5.0, 7.0, 10.0],
	"no": [0.0, 2.0, 4.0, 6.0, 8.0]
}
```