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详细说明： Auto-encoding is an important task which is typically re- alized by deep neural networks (DNNs) such as convolu- tional neural networks (CNN). In this paper, we propose En- coderForest (abbrv. eForest), the first tree ensemble based auto-encoder. We present a procedure for enabling forests to do backward reconstruction by utilizing the Maximal- Compatible Rule (MCR) defined by the decision paths of the trees, and demonstrate its usage in both supervised and unsupervised setting. Experiments show that, compared with DNN based aut o-encoders, eForest is able to obtain lower re- construction error with fast training speed, while the model itself is reusable and damage-tolerable ...展开收缩
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