11/8/2025

 11/8/2025

Today’s main task is to continue adjusting Coded OOS, and after completion, continue to study XGBoost model optimization.

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27/3/2025

 27/3/2025 Continue to study sales forecasting methods, focusing on learning and applying weighted moving average (WMA) for data analysis. In addition, analyze the sales during the same festival period (such as Hari Raya, Spring Festival, etc.) in historical data, compare the sales patterns of the same festival in different years, and identify the impact of festivals on sales. By calculating the sales share during the festival period, establish a forecasting model based on festival sales weights to more accurately estimate the sales of the upcoming holidays.
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13/6/2025

 13/6/2025 Today i continued to complete the work of integrating holiday factors into the sales forecasting model, and used the new model that included holiday information to predict sales, and then compared and analyzed the prediction results with the original prediction results that did not include holiday factors.
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9/4/2025

 9/4/2025 We will continue to study sales forecasting methods in depth. This time, we will focus on distinguishing national holidays from non-national holidays (non-national holidays, such as regional holidays or specific store promotion days) to analyze the actual impact of different types of holidays on sales in a more detailed manner. After completing the holiday classification and impact assessment, we will build a classification forecasting model based on the obtained data and apply it to sales forecasts for national and non-national holidays respectively.
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