Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 88-91.doi: 10.11896/j.issn.1002-137X.2017.11A.017

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Fast Incremental Learning Algorithm of SVM with Locality Sensitive Hashing

YAO Ming-hai, LIN Xuan-min and WANG Xian-bao   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In order to improve the training speed and the classification accuracy in large scale high dimension data,a new incremental learning algorithm of SVM with LSH was proposed.It uses the LSH algorithm,which can seek similar data fast in a large scale and high dimension data,to filter out the incremental samples which may become SVs on the basis of the SVM algorithm.Then it makes the selected samples and the existing SVs as a basis for the following training.We took advantages of the multiple data sets to validate the algorithm.Experiments show that this new algorithm can improve the speed of the incremental training learning in large scale data with the effective accuracy.

Key words: LSH,SVM,Incremental learning,Large scale data,High dimension

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