Last updated on Dec 16, 2024

Your predictive model's accuracy is questioned by end-users. How will you address their feedback?

When end-users doubt your model's accuracy, it's crucial to engage and rectify their concerns. To navigate this challenge:

Understand the context: Dive into the specific scenarios where the model underperformed according to users.

Improve communication: Clearly explain the model's capabilities and limitations to set realistic expectations.

Iterate and improve: Gather detailed feedback and use it to refine your model for better performance.

How do you turn skepticism into constructive dialogue around your predictive models?

+ Follow

Last updated on Dec 16, 2024

When end-users doubt your model's accuracy, it's crucial to engage and rectify their concerns. To navigate this challenge:

Understand the context: Dive into the specific scenarios where the model underperformed according to users.

Improve communication: Clearly explain the model's capabilities and limitations to set realistic expectations.

Iterate and improve: Gather detailed feedback and use it to refine your model for better performance.

How do you turn skepticism into constructive dialogue around your predictive models?

Rate this article