Based on prior knowledge, we know that age can be a significant factor in determining the presence of heart disease. 

To analyze the relationship between age and the presence of heart disease, we can group the data into two categories - 'no' indicating absence of heart disease and 'yes' indicating presence of heart disease. 

Let's assume a range of values for the age feature:
- 'no': Represents the absence of heart disease
- 'yes': Represents the presence of heart disease

After analyzing the data and considering individual cases, we can generate a dictionary with the appropriate age values for each target class.

```json
{
	"no": [40.0, 52.0, 56.0, 63.0, 68.0],
	"yes": [45.0, 51.0, 55.0, 60.0, 65.0]
}
```

Note: The specific age values provided above are examples and may vary depending on the dataset and patterns observed during analysis.