An organization is training a machine learning model to predict (Digital Leader)

Correct answer: A) Collect all weather data evenly across all cities.
I see, while collecting extreme weather data primarily from at-risk cities might provide a focused dataset for extreme events, it may not necessarily maximize prediction accuracy. The reason is that extreme weather events can occur in various locations, not just those deemed "at-risk" based on historical data or geographic factors. Therefore, collecting weather data evenly across all cities, including those with a history of extreme events and those without, ensures a more comprehensive dataset. This broader dataset allows the machine learning model to learn patterns and features from a diverse range of weather conditions, leading to potentially better prediction accuracy.