What Does The MAE Actually Telling me?
data-science, machine-learning
Solution
To be honest "in general" it tells you nearly nothing. The value is quite arbitrary, and only if you understand exactly your data you can draw any conclusions.
MAE stands for Mean Absolute Error, thus if yours is 1290 it means, that if you randomly choose a data point from your data, then, you would expect your prediction to be 1290 away from the true value. Is it good? Bad? Depends on the scale of your output. If it is in millions, then the error this big is nothing, and the model is good. If your output values are in the range of thousands, this is horrible.
If I understand correctly S&P 500 closing prices are numbers between 0 and 2500 (for last 36 years), thus error of 1290 looks like your model learned nothing. This is pretty much like a constant model, always answering "1200" or something around this value.
Problem
I've created a simple linear regression model to predict S&P 500 closing prices. then calculated the Mean Absolute Error (MAE) and got an MAE score of 1290. Now, I don't want to know if this is right or wrong but I want to know what MAE of 1290 is telling me about my model.