Not sure my understanding is correct, maybe you can shed some light. In a linear model, a higher coefficient for a feature, the more a feature played a role in making a prediction. However, when variables in a regression model are correlated, these conclusions don't hold anymore.
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That's a model without coefficients
Not sure my understanding is correct, maybe you can shed some light. In a linear model, a higher coefficient for a feature, the more a feature played a role in making a prediction. However, when variables in a regression model are correlated, these conclusions don't hold anymore.