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We present an efficient method for maintaining mixtures of prunings of a prediction or decision tree that extends the previous methods for "node-based" prunings () to the larger class of edge-based prunings. The method includes an online weight-allocation algorithm that can be used for prediction, compression and classification. Although the set of edge-based prunings of a given tree is much larger than that of node-based prunings, our algorithm has similar space and time complexity to that ofdoi:10.1145/267460.267487 dblp:conf/colt/PereiraS97 fatcat:tyl3mtpluratzgoejrbuhv7cqa