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Titlebook: Classification and Data Mining; Antonio Giusti,Gunter Ritter,Maurizio Vichi Conference proceedings 2013 Springer-Verlag Berlin Heidelberg

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Yimeei Guo,Weiwei Hu,Zhengzheng Fangems, there is even a goal conflict between consistency and robustness. This particularly applies to certain nonparametric statistical problems such as nonparametric classification and regression problems which are often ill-posed. As an example in statistical machine learning, support vector machine
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Security Problem and Solutions to M-commerceurbing effects of high dense areas we suggest a technique that selects a point in each cell of a grid defined along the Principal Component axes of the data. The selected sub-sample removes the high density areas while preserving the general structure of the data. Once the clustering on the gridded
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Yimeei Guo,Dongsheng Yan,Weiwan Zhanger to different occasions or positions in time or space, a comparative analysis of data stratified in batches can be suitable. The present approach combines clustering and factorial techniques to study the association structure of binary attributes over homogeneous subsets of data; moreover, it seek
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Security Problem and Solutions to M-commercend proprietary/legacy classifiers, like those used by banks for assessing the credit approvals, the data production and modeling is done locally, where only the local classifiers are available. In order to find a global classification rule, the ensemble classification paradigm proposes several metho
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