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A company is developing a system to moderate user-generated content in real-time. They have two predictive models: Model A is small, fast, and has 95% accuracy, while Model B is large, slow, and has 99.5% accuracy. The company observes that over 90% of the content is simple and easily classifiable. To optimize for both cost and performance, they decide to first process every piece of content with Model A. Only if Model A's confidence in its prediction is below a certain threshold is the content then passed to Model B for a final classification. What is the primary advantage of this two-step, conditional approach?
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A company is developing a system to moderate user-generated content in real-time. They have two predictive models: Model A is small, fast, and has 95% accuracy, while Model B is large, slow, and has 99.5% accuracy. The company observes that over 90% of the content is simple and easily classifiable. To optimize for both cost and performance, they decide to first process every piece of content with Model A. Only if Model A's confidence in its prediction is below a certain threshold is the content then passed to Model B for a final classification. What is the primary advantage of this two-step, conditional approach?
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