A modified SVM classification algorithm for data of variable quality

被引：0

作者：

Apolloni, Bruno ^{[1
]}

Malchiodi, Dario ^{[1
]}

Natali, Luca ^{[1
]}

机构：

[1] Univ Milan, Dipartimento Sci Informaz, Via Comel 39-41, I-20123 Milan, Italy

来源：

KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT III, PROCEEDINGS | 2007年 / 4694卷

关键词：

classification; data quality; SVM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a modified SVM algorithm for the classification of data augmented with explicit quality quantification for each example in the training set. As the extension to nonlinear decision functions through the use of kernels brings to a non-convex optimization problem, we develop an approximate solution. Finally, the proposed approach is applied to a set of benchmarks and contrasted with analogous methodologies in the literature.

引用

页码：131 / +

页数：2