1. This article describes the technical specifications of the chosen model by the platform. Once you have uploaded your dataset on the platform and generated the prediction report you need to navigate to the Tech Specs tab that gives all the metric values for the model chosen by the platform

    Here we can see that if you are not satisfied with the results you can reach out to us by clicking on the Book a Call tab. For the current dataset that we used we are getting great performance since the MAPE value is below 15%

  2. Next we look into the model metrics - it gives us the best performing Algorithm name that was chosen by the platform. The MAPE value of the model and how the performance of the model is via the performance indicator. We also have a brief review of the dataset such as the name, source and number of rows and the columns used

  3. Next section is the Advanced Model Metrics, where you’ll find all the details of the chosen model. These are standard metrics for any time series model - Testing RMSE, Mean Squared Error, Mean Absolute Error, Mean Absolute Percentage Error, Mean Scaled Error. Their corresponding values are listed next to them and their indicators (since all are error metrics the lower their values the better the performance). You have the option to download the advanced model metrics by using the download icon

  4. We have 7 main algorithms for time series forecasting - Holt Winters Multiplicative, Holt Winters Additive, ARIMA, SARIMA, PROPHET, XGBoost and ETS (Double Exponential Smoothing)

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