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Question 1 of 30
A retail company wants to enhance its sales forecasting by integrating a machine learning model into Power BI. The model predicts future sales based on historical data, seasonal trends, and promotional activities. After deploying the model, the company notices discrepancies between the predicted sales and actual sales figures. To address this, the data analyst decides to evaluate the model\'s performance using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). If the model\'s predictions yield an MAE of 150 units and an RMSE of 200 units, what can be inferred about the model\'s accuracy and reliability in the context of sales forecasting?
The model has a relatively high level of accuracy but may struggle with outliers.
The model is highly accurate and reliable for all sales predictions.
The model's predictions are consistently accurate across all data points.
The model is ineffective and should be discarded immediately.

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