The term "model-test-model" often refers to a process used in various fields such as machine learning, artificial intelligence, product development, and research. This iterative approach involves creating a model, testing its performance or efficacy, and then refining or re-engineering the model based on the results of the tests. Here are the general steps involved in the model-test-model process: 1. **Model Creation**: Initially, a model is developed based on existing theories, data, or hypotheses.
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