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CLASS CLASSIFICATION DEVICE, CLASS CLASSIFICATION METHOD AND CLASS CLASSIFICATION PROGRAM

机译:类的分类装置,类的分类方法和类的分类程序

摘要

PROBLEM TO BE SOLVED: To reduce computational complexity required for sparse expression class classification, and to quickly perform class classification without deteriorating classifying accuracy.;SOLUTION: In a class classification device 1, training data division means 11 divides training data obtained by class classification means 10 which performs sparse expression class classification into sensing matrix candidate data and verification data, and contribution rate calculation means 13 calculates the contribution rate of each candidate item included in the sensing matrix candidate data to correct classification, and sensing matrix creation means 14 creates a sensing matrix with the candidate item selected on the basis of the value of the contribution rate of the candidate item as a component, and sensing matrix updating means 15 updates the contribution rate of each candidate item included in the sensing matrix on the basis of the coefficient of a solution satisfying the linear constraint of the sensing matrix candidate data of the latest training data and verification data originating in the training data, and updates the sensing matrix on the basis of the value of the updated contribution rate.;COPYRIGHT: (C)2012,JPO&INPIT
机译:解决的问题:为了减少稀疏表达类别分类所需的计算复杂度,并在不降低分类精度的情况下快速执行类别分类。解决方案:在类别分类装置1中,训练数据划分装置11划分通过类别分类装置获得的训练数据参照图10,对感测矩阵候选数据和验证数据进行稀疏表达类别的分类,贡献率计算单元13计算该感测矩阵候选数据中包含的各候选项目的贡献率,以进行分类,感测矩阵生成单元14进行感测。基于候选项目的贡献率的值选择的候选项目作为成分的矩阵,感测矩阵更新装置15基于系数的系数更新感测矩阵中包括的每个候选项目的贡献率。满足线性约束的解决方案最新训练数据和源自训练数据的验证数据的感测矩阵候选数据的过滤器,并基于更新的贡献率的值更新感测矩阵。; COPYRIGHT:(C)2012,JPO&INPIT

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