An Improved SVM Based on Similarity Metric

Chaoyong Wang; Yanfeng Sun; Yanchun Liang

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An Improved SVM Based on Similarity Metric

机译：一种基于相似度量的改进支持向量机

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A novel support vector machine method for classification is presented in this paper. A modified kernel function based on the similarity metric and Riemannian metric is applied to the support vector machine. In general, it is believed that the similarity o

机译：提出了一种新的支持向量机分类方法。将基于相似度和黎曼度量的改进核函数应用于支持向量机。一般而言，我们认为

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《Journal of Universal Computer Science》 |2007年第10期|共9页
作者
Chaoyong Wang; Yanfeng Sun; Yanchun Liang;
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中图分类计算技术、计算机技术;
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机译：基于图的分组图像配准中改善变形一致性的新图像相似度量
3. Improving Graph-Based Image Segmentation Using Nonlinear Color Similarity Metrics [J] . L. E. Carvalho, S. L. Mantelli Neto, A. C. Sobieranski, International Journal of Image and Graphics . 2015,第4期

机译：使用非线性颜色相似性度量改进基于图的图像分割
4. Learning similarity metric with SVM [C] . Xiaoqiang Zhu, Pinghua Gong, Zengshun Zhao, Neural Networks (IJCNN), The 2012 International Joint Conference on . 2012

机译：使用SVM学习相似性指标
5. Investigation of a Kolmogorov complexity-based similarity metric for content-based image retrieval. [D] . Supamahitorn, Supat. 2004

机译：基于内容的图像检索基于Kolmogorov复杂度的相似性度量的研究。
6. Integrating species and interactions into similarity metrics: a graph theory-based approach to understanding community similarity [O] . Daniela N. López, Patricio A. Camus, Nelson Valdivia, -1

机译：将物种和相互作用整合到相似性度量中：一种基于图论的方法来理解社区相似性
7. Figure 4: (A) One conserved sequence, which occurs 79 times in 46,264 binding site peaks from the ChIP-seq data-set. The mutation profile of this conserved sequence is illustrated, where ’_ ’ indicates this base is unchanged; DEL indicates this base is lost; INS X indicates a new base X is inserted in front of this base. (B) Several repeated elements patterns are listed. (C) In the first column, the top five DNA motifs, mined by meme-chip tools (Machanick Bailey, 2011) are illustrated. The resemblant conserved sequences, found by the CFSP algorithm are listed in the second column. In the third column, the position-specific scoring matrices, which are transformed from mutational information are listed. The similarity between meme motif and resemblant conserved sequence with PSSM format was calculated via a stamp motif comparison tool (Mahony Benos, 2007). The E-values for the similarity of those pairs is displayed in the fourth column. (D) One motif is selected in each group clustered by gkmsvm descriptors, and the corresponding motif found by the CFSP algorithm is listed below. (E) There are additional datasets (File No: ENCFF100GRL, ENCFF616IRT, ENCFF870CER, Target: SREBF1) collected from https://www.encodeproject.org. The top two motifs are selected in each file using meme tools, and the corresponding motifs found by our algorithm are listed below. [O] . -1

机译：图4：（a）一种保守序列，其发生在芯片-SEQ数据集中的46,264个结合位点峰值中的79倍。说明了这种保守序列的突变分布，其中'_'表示该碱度不变; del表示此基础丢失; INS X表示新的基础X插入此基础前面。（b）列出了几种重复的元素模式。（c）在第一栏中，示出了由MEME芯片工具（Machanick＆Bailey，2011）开采的前五个DNA主题。由CFSP算法发现的相应保守序列列于第二列中。在第三列中，列出了从突变信息转换的特定位置的评分矩阵。 MEME主题与PSSM格式的相似性与PSSM格式之间的相似性通过邮票图章比较工具（Mahony＆Benos，2007）计算。这些对相似性的电子值显示在第四列中。（d）在由GKMSVM描述符聚集的每个组中选择了一个图案，下面列出了CFSP算法的相应主题。（e）从https://www.encodeproject.org收集的，有附加数据集（文件no：cernff100grl，cenf616irl，conf8.20cer，target：srebf1）。使用MEME工具在每个文件中选择前两个图案，并且我们的算法发现的相应主题如下所示。
8. Metric Similarity in Vegetation-Based Wetland Assessment Methods. [R] . Mack, J. J., Kentula, M. E. 2010

机译：基于植被的湿地评价方法的度量相似性。

An Improved SVM Based on Similarity Metric

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