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One-Class-at-a-Time Removal Sequence Planning Method for Multiclass Classification Problems

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4 Author(s)
Chieh-Neng Young ; Dept. of Mech. Eng. & Electro-Mech. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung ; Chen-Wen Yen ; Yi-Hua Pao ; Nagurka, M.L.

Using dynamic programming, this work develops a one-class-at-a-time removal sequence planning method to decompose a multiclass classification problem into a series of two-class problems. Compared with previous decomposition methods, the approach has the following distinct features. First, under the one-class-at-a-time framework, the approach guarantees the optimality of the decomposition. Second, for a K-class problem, the number of binary classifiers required by the method is only K-1. Third, to achieve higher classification accuracy, the approach can easily be adapted to form a committee machine. A drawback of the approach is that its computational burden increases rapidly with the number of classes. To resolve this difficulty, a partial decomposition technique is introduced that reduces the computational cost by generating a suboptimal solution. Experimental results demonstrate that the proposed approach consistently outperforms two conventional decomposition methods

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Neural Networks, IEEE Transactions on  (Volume:17 ,  Issue: 6 )