【摘要】：針對糾錯輸出編碼分解框架的自身特點、從降低誤判風險出發(fā),研究了帶拒絕域的ECOC多類分類方法.首先在二類劃分過程中引入拒絕域,對不屬于正負子類的待識別樣本進行拒識;其次,在基分類器內(nèi)部引入拒絕域,以最小化風險貝葉斯決策為目標,利用后驗概率輸出和代價矩陣尋找拒絕域閾值,對樣本輸出值落入拒絕域中的樣本進行拒識;最后,研究了不同拒絕域輸出的解碼方法,并討論了拒識碼字個數(shù)和矩陣最小Hamming距離之間的關(guān)系.實驗結(jié)果表明基于二類劃分構(gòu)造的拒絕域能夠提高分類正確率,而基于基分類器構(gòu)造的拒絕域能夠減小分類代價.
[Abstract]:In view of the self-feature of the error correction output code decomposition framework, the ECOC multi-class classification method with the rejection domain is studied from the point of reducing the risk of misjudgment. the method comprises the following steps of: firstly, introducing a refusal domain in a second-class division process, and rejecting a sample to be identified which does not belong to the positive and negative subclasses; secondly, introducing a rejection domain into the base classifier to minimize the risk Bayesian decision as a target, and searching for a rejection domain threshold by using a posterior probability output and a cost matrix, Finally, the method of decoding the output of different denied domains is studied, and the relation between the number of rejected codes and the minimum Hamming distance of the matrix is also discussed. The experimental results show that the classification accuracy can be improved based on the refusal domain of the second-class partition structure, and the classification cost can be reduced based on the refuse field constructed by the base classifier.
【作者單位】： 空軍工程大學防空反導學院;空軍工程大學信息與導航學院;空軍大連通信士官學�；A(chǔ)部;
【基金】：國家自然科學基金(No.61273275,No.61503407)
【分類號】：TP181

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