When preparing a dataset for a predictive model in a retail business, what preprocessing steps are critical to handle the seasonality in sales data?
- Data Normalization
- Feature Scaling
- One-Hot Encoding
- Time Series Decomposition
Time series decomposition is crucial for handling seasonality in sales data. It involves breaking down the time series into its trend, seasonality, and residual components, allowing the model to capture the underlying patterns.
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