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The calibration factor method based on a negative binomial model was employed to compare its predictive performance with that of the transfer learning technique. Mean square error was calculated to evaluate the prediction accuracy. Two cities in China, Shanghai and Guangzhou, were taken mutually as source data domain and target data domain. Results showed that the models constructed with TrAdaBoost.R2 had better prediction accuracy than the conventional calibration method. The TrAdaBoost.R2 is recommended due to its predictive performan
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