So, I'm kinda new to machine learning and I was trying to predict the monthly sales of a business using a set of features and using a sliding window of the past sales of 12 months.
I used some algorithms to do it, including linear/polynomial regression, lasso/elastic and SVR. I got the best results with elastic regression resulting in the following result:
As it shows, the model fit the mean of the curve somewhat well, but I would like it to fit the variance as well. So, I've been searching what technique or feature to use could better fit my data, but I still found nothing precise.
Would someone knows what could I do to to take the variance of the system into account?
Thanks in advance!