南京大学学报（自然科学版）Issue(1)：139-147,9.DOI:10.13232/j.cnki.jnju.2015.01.020
一种基于正则化最小二乘的多标记分类算法
A multi-label classification algorithm based on regularized least squares
摘要
Abstract
In traditional supervised learning,each obj ect is represented by a single instance and associated with only one class label.Recently,multi-label learning attracts much attention from researchers of machine learning,pattern recognition etc.,due to its ability in obtaining more information on predicting multiple class labels.In multi-label learning,each obj ect is represented by an instance,while it may be assigned to multiple class labels simultaneously. Hence,its task is to predict a class label set for the unknown instance.The resulting model is usually an ill-conditioned quadratic program,which requires regularization.In this paper,a multi-label classification algorithm based on regularized least squares classification is proposed,which is derived from the traditional regularized least squares classification.To establish our model,we first transform the multi-label learning problem into multiple inde-pendent binary classification problems (each for one class label).Then,in order to fully exploit the class label correlations information,an adjacent graph based on all the class labels is built,where each node stands for one class label and the weight of each edge reflects the similarity between corresponding pairwise-label.Finally,a multi-label regularized least squares model is constructed on the basis of kernel function,whose first order optimality condition is a Sylvester equation,which can be solved efficiently by using numerical linear algebra technique.We perform experiment on eight benchmark data sets in terms of five different evaluation criteria and compare it with the other six state-of-the-art multi-label learning algorithms.The results show that our algorithm is competitive.关键词
多标记学习/正则化最小二乘分类/二分类问题/核函数/Sylvester方程Key words
multi-label learning/regularized least squares classification/binary classification problem/kernel function/Sylvester equation分类
信息技术与安全科学引用本文复制引用
吕静,何志芬..一种基于正则化最小二乘的多标记分类算法[J].南京大学学报（自然科学版）,2015,(1):139-147,9.基金项目
江苏省自然科学基金重点重大专项(BK2011005) （BK2011005）
