Fast Pattern Selection Algorithm for Support Vector Classifiers: Time Complexity Analysis
نویسندگان
چکیده
Training SVM requires large memory and long cpu time when the pattern set is large. To alleviate the computational burden in SVM training, we propose a fast preprocessing algorithm which selects only the patterns near the decision boundary. The time complexity of the proposed algorithm is much smaller than that of the naive M algorithm
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