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Predictive models are statistical models whose primary purpose is to predict other observations of a system optimally, as opposed to models whose purpose is to test a particular hypothesis or explain a phenomenon mechanistically. As such, predictive models place less emphasis on interpretability and more emphasis on performance.
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Machine learning models with high test set variance?
Do certain machine learning algorithms have higher variance in their predictions than others or have parameters to adjust this? Right now I'm using a regularized linear model for time series predictio …
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Models that train on Mean Absolute Error or similar?
I'm trying to do time series prediction and I'm interested in training on MAE or other custom loss functions. For my problem I'd prefer having errors of {0, 10, 0, 10, 0, 10} as supposed to {5, 5, 5, …
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How does heteroscedasticity relate to predictive accuracy?
I understand that heteroscedasticity leads to problems with coefficient estimates of a model, but I'd like to know how it relates to predictive accuracy. After creating my original linear model, I am …