Finding the best not the most: regularized loss minimization subgraph selection for graph classification
Our algorithm selects the optimal subgaphs for graph classification. We generalize the column generation technique of gBoost for graph classification. We use the elastic net to produce sparse and robust solutions for subgraph selection. We derive an effective pruning rule for search space reduction. We demonstrate the effectiveness of our algorithm.
graph classification classification feature selection sparse learning