Fig. 1
From: Deciding when to stop: efficient experimentation to learn to predict drug-target interactions
The major components of an active learning framework. The entries of the matrix are color coded: label not known (light gray), interaction (black), no interaction (white). At initialization a subset of known labels for the interactions matrix and the drug and target kernels K d and K t are provided. In each round of the active learning algorithm, the labels of the entire interaction matrix are predicted and used to determine which labels to query next. In this figure, the dark red values represent a high probability for a hit, whereas the dark blue values represent a high probability for a miss