I'm pretty confident on this one. Adaptive models learn from both positive and negative outcomes, which allows them to adjust and improve over time. That's the main distinction from a static predictive model. Option C is my choice.
Ah, I see the key difference now. Adaptive models consider both symbolic and numeric predictors, while predictive models may be limited to one or the other. I'll select option B.
Okay, I think I've got this. Adaptive models can use strategy properties as predictors, which is different from a standard predictive model. I'll go with option A.
Hmm, I'm a bit unsure about this. I know adaptive models are supposed to be more flexible, but I'm not sure exactly how they differ from predictive models.
Option C seems to be the correct answer. An adaptive model learns from both positive and negative outcomes, unlike a predictive model which may only consider positive outcomes.
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