A data scientist is designing a real-time machine-learning model that classifies a user based on initial behavior. The run times of these models are provided in the following table: Which of the…

The correct answer is B. Random forest. For a real-time application, inference latency is critical. Although its accuracy (88%) is slightly lower than the others, the random forest's 1-minute run time is by far the fastest, making it the only model capable of meeting real-time responsiveness.

Machine Learning

Question

A data scientist is designing a real-time machine-learning model that classifies a user based on initial behavior. The run times of these models are provided in the following table:

Which of the following models should the data scientist recommend for deployment?

Exhibit

Options

AXGBoost
BRandom forest
CDecision trees
DArtificial neural network

How the community answered

(52 responses)

A
12% (6)
B
81% (42)
C
6% (3)
D
2% (1)

Explanation

For a real-time application, inference latency is critical. Although its accuracy (88%) is slightly lower than the others, the random forest's 1-minute run time is by far the fastest, making it the only model capable of meeting real-time responsiveness.

Topics

#model selection#real-time inference#deployment constraints#random forest

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