60 results about "Class prediction" patented technology

The invention discloses a federated learning data privacy protection method and system based on gradient perturbation, and belongs to the field of data privacy protection, and the method comprises the steps: carrying out the class prediction of a sample in a data participant through a local model after federated learning training, and obtaining an original prediction probability vector; disturbing the original prediction probability vector to obtain a disturbance prediction probability vector, wherein the prediction label of the disturbance prediction probability vector is the same as the prediction label of the original prediction probability vector, and the angular deviation of the gradient of the prediction loss function relative to the gradient of the prediction loss function of the original prediction probability vector is maximum; retraining each local model by taking the minimum difference between the original prediction probability vector and the disturbance prediction probability vector of each local model as a target; and aggregating the retrained local models to obtain a global model. The protected federal learning global model can effectively reduce the risk that the model prediction output and the model gradient leak the privacy of the user participants on the premise of maintaining the availability of the model.

The invention discloses a protein structure class prediction method based on weighted composition position vectors and a support vector machine. Firstly, protein structure class normal data sets are selected or established, weighting factors are introduced based on composition position vectors, and to-be-predicted protein sequences are represented through the weighted composition position vectors; the weighted composition position vectors are combined with the support vector machine, and the protein structure class prediction method is established through a direct multiclass classification strategy. According to the method, information of amino acid compositions is contained, position information of each amino acid residue in the protein sequences is also contained, the one-to-one correspondence function relation is formed between the position information and the protein sequences, the weighting factors are introduced to the composition position vector representation method, and prediction accuracy can be obviously improved by means of adjusting the weighting factors. The method is simple, rapid and sensitive, and is expected to be applied to other protein prediction fields.