Certified Machine Learning Professional Exam

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Question 1

Which of the following describes concept drift?

Concept drift is when there is a change in the distribution of an input variable

Concept drift is when there is a change in the distribution of a target variable

Concept drift is when there is a change in the relationship between input variables and target variables

Concept drift is when there is a change in the distribution of the predicted target given by the model

None of these describe Concept drift

Correct Answer: C

Concept drift refers to a change in the relationship between input variables and target variables over time. This change can cause the model's predictions to become less accurate as the original relationship the model learned is no longer valid. It is not merely a shift in the distribution of input or target variables but specifically in how they relate to each other.

Discussion

BokNinjaOption: C

C. Concept drift is when there is a change in the relationship between input variables and target variables. Concept drift refers to the situation when the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes the model to become less accurate as time passes.

nnn_666Option: C

concept drift or drift is an evolution of data that invalidates the data model

ADVITOption: C

Answer is C

hugodscarvalhoOption: C

Concept drift is a change in the underlying relation between the data and the label. Doc: https://docs.deepchecks.com/stable/general/guides/drift_guide.html#concept-drift

random_data_guyOption: C

agree with BokNinja - C should be correct

OreocakeOption: C

C is correct

zafarsohaibOption: C

Answer is C. Concept drift is a change in the relationship between the input data and the model target.

sindhu_gowdaOption: C

Answer is C

c4b65b5Option: C

C is correct