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Multivariate Time series forecasting

Abstract

The project goal was to accurately predict the amount of printing volume per printer per day.

Challenges

Learning to find the correct time series model to accurately predict the printing volume.
Dealing with large quantities of data.

Achievements (according to KPIs)

Improved the naïve model by 6%.
The improvement is by comparing average absolute error printed volume divided by the mean printed volume.
The naïve model had a 53% error ratio.
My model had a 47% error ratio.