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Can I use a fitted polynomial regression to make reverse predictions?
Yes, you can use a fitted polynomial regression model to make reverse predictions, also known as back-predictions or extrapolations.
However, it's important to note that the accuracy of these reverse predictions can be unreliable, especially when you are extrapolating beyond the range of the input values that the model was trained on. This is because the model is essentially "guessing" what the output would be for input values that it has not seen before, and its performance is likely to degrade the further it gets from the range of values it was trained on.
So, if you want to use a polynomial regression model for reverse predictions, it's important to carefully consider the range of input values that you will be using and how far outside the range of the training data you will be extrapolating. It's also a good idea to assess the accuracy of the model on a holdout set of data or through cross-validation and to be aware of the limitations of the model when making predictions outside of its range of training data.
Running random forest algorithm with one variable