What are generative attributes? How are they different from standard features / attributes?

Answer:

Generative attributes are new input variables derived from the original model dataset that are contenders for being selected as features in machine learning models. Click They are also commonly known as engineered features.

These features exist because the way we model data for analytic purposes is often different from how we want data structured for machine learning.

• A standard non-generative attribute is something about a person (or job or anything else you're making predictions for) at a point in time, such as their salary or manager’s name.
• A generative attribute can be a count of events such as # of promotions over the last 5 years, a flag if a person meets a set of criteria such as quality hire, or a higher level aggregation such as team or location such as team headcount.

Configuring Generative Attributes in the One AI Query Builder

Examples of Generative Attributes

• Team Headcount
• Number of Plant Safety Incidents
• Number of Promotions for the Last 3 Years
• Team Average Performance
• Team Average Tenure
• Demotions for All Time, Binary

Check out this One AI Generative Attributes help article for more information and guidance on how to build them.