Which ONE of the following tests is MOST likely to describe a useful test to help detect different kinds of biases in ML pipeline?

The correct answer is B. Test the model during model evaluation for data bias. This is a critical stage where the model is evaluated to detect any biases in the data it was trained on. It directly addresses potential data biases in the model.

Testing, Debugging, and Deployment

Question

Options

ATesting the distribution shift in the training data for inappropriate bias.
BTest the model during model evaluation for data bias.
CTesting the data pipeline for any sources for algorithmic bias.
DCheck the input test data for potential sample bias.

How the community answered

(23 responses)

A
17% (4)
B
70% (16)
C
9% (2)
D
4% (1)

Explanation

This is a critical stage where the model is evaluated to detect any biases in the data it was trained on. It directly addresses potential data biases in the model.

Topics

#bias detection#ML pipeline#data bias#model evaluation

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