SupplementaryMaterialsVIME: ExtendingtheSuccessofSelf-and Semi-supervisedLearningtoTabularDomain

Semisupervised learning uses the trained encoder in learning a predictive model on both labeled and unlabeleddata. Figure 3: The proposed data corruption procedure. Original feature matrix(X) consists of four samples xi,i = 1...,4, where each row/column represents a sample/feature, and the features in each sample are represented by the same color. In the experiment section of the main manuscript, we evaluate VIME and its benchmarks on 11 datasets(6genomics,2clinical,and3publicdatasets). The selected SNPs and the corresponding blood cell trait together form an independent labeled dataset.