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PROACTIVELY PREDICTING TRANSACTION QUANTITY BASED ON SPARSE TRANSACTION DATA
PROACTIVELY PREDICTING TRANSACTION QUANTITY BASED ON SPARSE TRANSACTION DATA
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机译:主动预测基于稀疏事务数据的交易量
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摘要
The present disclosure involves systems, software, and computer implemented methods for proactively predicting demand based on sparse transaction data. One example method includes receiving a request to predict transaction quantities for a plurality of transaction entities for a future time period. Historical transaction data for the transaction entities is identified for a plurality of categories of transacted items. The plurality of categories are organized using a hierarchy of levels. Multiple levels of the hierarchy are iterated over starting at a lowest level. For each current level in the iteration, features to include in a quantity forecasting model for the current level are identified. The quantity forecasting model is trained using the identified features.;Predicted transaction dates are predicted for the current level by a transaction date prediction model. The quantity forecasting model is used to generate predicted quantity information for the current level for the predicted transaction dates.
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