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Distance Metric Learning-Based Conformal Predictor

Abstract : In order to improve the computational efficiency of conformal predictor, distance metric learning methods were used in the algorithm. The process of learning was divided into two stages: offline learning and online learning. Firstly, part of the training data was used in distance metric learning to get a space transformation matrix in the offline learning stage; Secondly, standard CP-KNN was conducted on the remaining training data with a nonconformity measure function defined by K nearest neighbors classifier in the transformed space. Experimental results on three UCI datasets demonstrate the efficiency of the new algorithm.
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Fan Yang, Zhigang Chen, Guifang Shao, Huazhen Wang. Distance Metric Learning-Based Conformal Predictor. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.254-259, ⟨10.1007/978-3-642-33412-2_26⟩. ⟨hal-01523097⟩



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