An airline has created a ML model to project fuel requirements for future flights. The model imports weather data such as wind speeds and temperatures, calculates flight routes based on historical routings from air traffic control, and estimates loads from average passenger and baggage weights. The model performed within an acceptable standard for the airline throughout the summer but as winter set in the load weights became less accurate. After some exploratory data analysis it became apparent that luggage weights were higher in the winter than in summer. Which of the following statements BEST describes the problem and how it could have been prevented?

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A. The model suffers from drift and therefore should be regularly tested to ensure that any

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B. The model suffers from drift and therefore the performance standard should be eased until a new

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C. The model suffers from corruption and therefore should be reloaded into the computer system

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D. The model suffers from a lack of transparency and therefore should be regularly tested to ensure

An airline has created a ML model to project fuel requirements for future flights. The model imports weather data such as wind speeds and temperatures, calculates flight routes based on historical…

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