Forecasting Rossmann Store Leading 6-month Sales
نویسندگان
چکیده
We investigated the comparative performance of Frequency Domain Regression (FDR) and Support Vector Regression (SVR) for time-series prediction of Rossman Store Sales. Due to the extent of the data variables provided, SVR clearly outperformed FDR. Within SVR, our results reviewed that a polynomial kernel with regularization is most effective.
منابع مشابه
Rossmann Store Sales
The objective of this project is to forecast sales in euros at 1115 stores owned by Rossmann, a European pharmaceutical company. The input to our algorithm is a feature vector (discussed in section 3) of a single day of data for that store. We tried using a number of algorithms, but mainly gradient boosting, to output the predicted total sales in euros for the given store that day. Rossmann pro...
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