An ML team wants to prevent its model from favoring one gender or region. Which characteristic should its training dataset emphasize to achieve this goal?
Encrypting all data at rest
Training only on recently collected data
A high compression ratio of the data
Inclusivity and diversity among samples
A dataset that is inclusive and diverse contains sufficient examples from every relevant gender, age group, region, and other demographic attributes. This balance reduces the chance that the model will learn patterns that only apply to a dominant subgroup, helping to mitigate bias and improve generalization across all users. Merely compressing data, encrypting it, or limiting the time range of the data does not address representation gaps and therefore will not, by itself, prevent demographic favoritism.
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
All IT & Cybersecurity Package plans include the following perks and exams .
Our pricing is simple. Full access to all certifications and exams in each package, for one price.
As many practice tests for as many topics as you want.
Use study mode non-stop, no limits.
Access to our AI assistant, Bash, trained to help you pass your exam.
Track your scores over time in study mode and report cards.
See how you improve over time, and where you need to focus.
Access our store with even bigger discounts than before.
Unlimited access to all performance questions and be prepared for the real thing.
All IT & Cybersecurity Package plans include unlimited access to the following study materials.
Create an account or sign in to access our study materials.