Extended Data Fig. 2: Model design and training architecture. | Nature Biotechnology

Extended Data Fig. 2: Model design and training architecture.

From: Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms

Extended Data Fig. 2

a) Illustration of Logistic Regression (LR) and signature scoring models, hyperparameters and outputs (see Methods). The tables describe the 21 models. b) Illustration of the nested-cross-validation framework to train and evaluate the models. Here we adapt a leave-one-patient-out approach to better simulate the model performance on new data from a new patient (see Methods). In box plots, the boxes represent the median and the interquartile range (IQR), while the whiskers extend to 1.5 times the IQR.

Back to article page