Based on prior knowledge, it is generally expected that exercise-induced angina (ExerciseAngina) is positively associated with the presence of heart disease. This means that if a patient experiences exercise-induced angina, it is more likely that the coronary angiography will show a heart disease.

To analyze the relationship between the feature and the task, we need data that includes exercise-induced angina values and the corresponding coronary angiography results. With this data, we can examine the distribution of exercise-induced angina values for each target class (heart disease present or heart disease not present).

Based on the task, the dictionary will have two keys: "no" and "yes". We will populate the values of each key with the observed exercise-induced angina values corresponding to the target class. The exercise-induced angina values will be represented as strings in lists.

Here's the dictionary in requested format:

```json
{
	"no": ["N"],
	"yes": ["Y"]
}
```

Please note that it is assumed that "N" represents the absence of exercise-induced angina and "Y" represents the presence of exercise-induced angina. If there are any other values for ExerciseAngina, they will not be included in the dictionary unless they are observed for the respective target classes.