Exam DP-100 topic 5 question 23 discussion

model, feature, metric (just switch a and b in answer area)

The three actions that you should perform in sequence to use the Fairlearn dashboard to assess fairness in a selected model are: Select a binary classification or regression model: Fairlearn is a toolkit for assessing and improving fairness in binary classification and regression models. Therefore, you need to select a model that falls into one of these two categories. Select a metric to be measured: After selecting the model, you need to choose a metric to be measured. Fairlearn provides a range of fairness metrics, such as demographic parity, equalized odds, and equal opportunity, that can be used to assess how the model performs across different groups. Select a model feature to be evaluated: Once you have selected the model and the metric, you need to choose a model feature to be evaluated. This could be any feature that you believe may have an impact on the fairness of the model, such as race, gender, or age. You can use Fairlearn to analyze the model's performance across different subgroups based on this feature.

Fairlearn works with binary classification or regression models, so you need to select one of these first. Next, you need to choose what metric you want to use to measure fairness. Finally, you select which feature of the model you want to evaluate for fairness.

model, feature, metric https://youtu.be/1Au1z9CtLq4?si=lIJumgmRfsC7Ad2V&t=2346

On exam 18-06-22

it can be only binary classifier or regression model select a feature select a performance metric select a fairness metric

on exam 18/03/2022