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An accurate tumor classification is important to diagnosis and treatment cancers. The conventional methods for tumor classification include training and testing phases, which may cause over fitting. Although this problem can be avoided by using sparse representation classification, the existing sparse representation methods for tumor classification are inefficient. In this paper, an efficient and...
Along with the increase number of users for the credit, the screening of applicants becomes very significant. If the credit of applicants is bad, the bank will obtain a great loss. Support vector machine (SVM) is one of the most popular kinds of algorithms for the new consumer's credit approval. However, there is a disadvantage that the more close to the optimal hyper plane, the greater possibility...
At present, only the single-factor is usually used in the process of non-stationary time series regression prediction based on Support Vector Machines thus inducing weak generative ability. To solve this problem, the concept of multi-factors is introduced in this paper. The problem of choosing the appropriate multi-factors used for elevating prediction ability is solved in this paper. And the paper...
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