made the prompt for generating explanations more detailed

[leowjli]

No description provided.

[ai-pull-request-review-agent]

main.py

Provide more detailed and actionable guidance for generating the explanation.
Create Issue

    - If the customer has over a 40% risk of churning, generate a 3 sentence explanation of why they are at risk of churning. 
      For instance, consider that:
        - If the customer has a low account balance or low tenure, they might be more likely to leave the bank, as churned customers may exhibit similar traits.
        - If the customer is an inactive member (e.g., not using many bank products), this may align with trends seen in the churned group.
        - Pay attention to feature importance to indicate which factors matter most in the prediction, such as whether they have multiple products, are active, or belong to certain geographical regions.
    - If the customer has less than a 40% risk of churning, generate a 3 sentence explanation of why they might not be at risk of churning. 
      - If the customer has multiple products and is an active member, they are less likely to churn, as these features are commonly linked with retention.
      - A higher account balance, longer tenure, or a high credit score may suggest the customer is more financially stable, which often correlates with a lower churn risk.
      - Again, take into account the feature importance ranking to explain why these characteristics suggest loyalty.

[ai-pull-request-review-agent]

Provide more detailed and actionable guidance for generating the explanation.

Suggested change

	- If the customer has over a 40% risk of churning, generate a 3 sentence explanation of why they are at risk of churning.
	For instance, consider that:
	- If the customer has a low account balance or low tenure, they might be more likely to leave the bank, as churned customers may exhibit similar traits.
	- If the customer is an inactive member (e.g., not using many bank products), this may align with trends seen in the churned group.
	- Pay attention to feature importance to indicate which factors matter most in the prediction, such as whether they have multiple products, are active, or belong to certain geographical regions.
	- If the customer has less than a 40% risk of churning, generate a 3 sentence explanation of why they might not be at risk of churning.
	For instance, consider that:
	- If the customer has multiple products and is an active member, they are less likely to churn, as these features are commonly linked with retention.
	- A higher account balance, longer tenure, or a high credit score may suggest the customer is more financially stable, which often correlates with a lower churn risk.
	- Again, take into account the feature importance ranking to explain why these characteristics suggest loyalty.
	- If the customer has over a 40% risk of churning,
	generate a 3 sentence explanation of why they are at risk of churning.
	For instance, consider that:
	- If the customer has a low account balance or low tenure, they might be more likely to leave the bank, as churned customers may exhibit similar traits.
	- If the customer is an inactive member (e.g., not using many bank products), this may align with trends seen in the churned group.
	- Pay attention to feature importance to indicate which factors matter most in the prediction, such as whether they have multiple products, are active, or belong to certain geographical regions.
	- If the customer has less than a 40% risk of churning, generate a 3 sentence explanation of why they might not be at risk of churning.
	- If the customer has multiple products and is an active member, they are less likely to churn, as these features are commonly linked with retention.
	- A higher account balance, longer tenure, or a high credit score may suggest the customer is more financially stable, which often correlates with a lower churn risk.
	- Again, take into account the feature importance ranking to explain why these characteristics suggest loyalty.