Answer-first summary for fast verification
Answer: The label data must be whole numbers., The label data must be a positive value.
Poisson regression is specifically designed for modeling count data, which must be non-negative integers (whole numbers). The label data (number of calls) represents counts, so it must be whole numbers (B) and cannot be negative, meaning it must be positive values (D). Option A is incorrect because negative values are invalid for count data. Option C is incorrect because count data is discrete, not non-discrete. Option E is incorrect because while whole numbers can be zero or positive, negative values are not allowed in Poisson regression.
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You are building a regression model to estimate the number of calls during an event. You need to verify if the feature set meets the requirements for a Poisson regression model.
Which two conditions must the feature set satisfy? Each correct answer presents part of the solution.
A
The label data must be a negative value.
B
The label data must be whole numbers.
C
The label data must be non-discrete.
D
The label data must be a positive value.
E
The label data can be positive or negative.