Which data concept describes changes in the relationship between inputs and outputs over time?

Which data concept describes changes in the relationship between inputs and outputs over time?

• A. Data drift
• B. Training data
• C. Concept drift
• D. Validation data

Answer: (C)

Concept drift is when the relationship between inputs and the target output changes over time. This means the mapping the model has learned from features to predictions no longer matches current reality, so the same inputs can imply different outputs than before. This is different from data drift, which is a shift in the distribution of the input features themselves, not necessarily a change in how those inputs relate to the output. It’s also not about the data used for training or validation. An example is a spam filter: if spammers adopt new language patterns, the way certain words map to “spam” changes over time, illustrating concept drift.

Concept drift is when the relationship between inputs and the target output changes over time. This means the mapping the model has learned from features to predictions no longer matches current reality, so the same inputs can imply different outputs than before. This is different from data drift, which is a shift in the distribution of the input features themselves, not necessarily a change in how those inputs relate to the output. It’s also not about the data used for training or validation. An example is a spam filter: if spammers adopt new language patterns, the way certain words map to “spam” changes over time, illustrating concept drift.