Fig. 1
From: Predicting lncRNA and disease associations with graph autoencoder and noise robust gradient boosting
The pipeline for LDA prediction with LDA-GARB. (i) Feature extraction. Linear and nonlinear features of lncRNAs and diseases are extracted by NMF and GAE. And each LDA is depicted as a vector through concatenating the learned linear and nonlinear features. (ii) LDA classification. The noise-robust gradient boosting model is designed to classify unobserved LDAs based on the extracted LDA features..
