Aumento de la confianza en la interpretación del PET con 18F-Florbetaben: “machine learning” basado en la aproximación cuantitativa

Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

“…By using stochastic gradient descent for model parameter optimization, the BPLR algorithm can gradually reduce the loss function and improve the fit of the model on the training set, so as to achieve better personalized sorting results. In practical applications, different optimization algorithms and the addition of regularization terms can also be used to further improve the model performance and generalization ability [7]. In addition, reasonable setting of hyperparameters such as learning rate and batch size is also key to optimizing the model.…”