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2112results about "Ensemble learning" patented technology

Model parameter training method, terminal, system and medium based on federated learning

ActiveCN109492420AImprove predictive abilityFeature Space ExpansionEnsemble learningCharacter and pattern recognitionCharacteristic spaceModel parameters
The invention discloses a model parameter training method based on federal learning, a terminal, a system and a medium, and the method comprises the steps: determining a feature intersection of a first sample of a first terminal and a second sample of a second terminal, training the first sample based on the feature intersection to obtain a first mapping model, and sending the first mapping modelto the second terminal; receiving a second encryption mapping model sent by a second terminal, and predicting the missing feature part of the first sample to obtain a first encryption completion sample; receiving a first encrypted federal learning model parameter sent by a third terminal, training a to-be-trained federal learning model according to the first encrypted federal learning model parameter, and calculating a first encryption loss value; sending the first encryption loss value to a third terminal; and when a training stopping instruction sent by the third terminal is received, takingthe first encrypted federal learning model parameter as a final parameter of the federal learning model to be trained. According to the invention, the characteristic space of two federated parties isexpanded by using transfer learning, and the prediction capability of the federated model is improved.
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