Based on prior knowledge, high serum cholesterol levels are often associated with an increased risk of heart disease. Therefore, we can expect that higher cholesterol levels may be more common in patients with heart disease (target class 'yes') compared to those without heart disease (target class 'no').

To analyze the relationship between the feature (Cholesterol) and the task (presence of heart disease), we can examine the distribution of cholesterol values for each target class. By selecting typical cholesterol values for both target classes, we can observe the pattern:

```json
{
	"no": [140.0, 160.0, 180.0, 200.0, 220.0], 
	"yes": [220.0, 240.0, 260.0, 280.0, 300.0] 
}
```

In this example, the cholesterol values for the 'no' class range from 140 to 220 (in mm/dl), while for the 'yes' class, the values range from 220 to 300 (in mm/dl). These values are hypothetical and can be adjusted based on specific knowledge or data distribution.