已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Two‐stage‐neighborhood‐based multilabel classification for incomplete data with missing labels

缺少数据 模式识别(心理学) 特征(语言学) 人工智能 相似性(几何) 计算机科学 数据挖掘 模糊逻辑 功能(生物学) 核(代数) 数学 机器学习 图像(数学) 语言学 进化生物学 生物 组合数学 哲学
作者
Lin Sun,Tianxiang Wang,Weiping Ding,Jiucheng Xu,Anhui Tan
出处
期刊:International Journal of Intelligent Systems [Wiley]
卷期号:37 (10): 6773-6810 被引量:19
标识
DOI:10.1002/int.22861
摘要

In recent years, it has been difficult for multilabel classification to obtain complete multilabel data in real-world applications, and even a large number of labels for training samples are randomly missed. As a result, the classification task of incomplete multilabel data with missing labels faces formidable challenges. This paper presents a two-stage-neighborhood-based multilabel classification method for incomplete data with missing labels in neighborhood decision systems. First, to solve the problem of selecting the neighborhood radius manually, as well as balancing the samples in the neighborhood, the neighborhood radius based on the feature distribution function is defined, and the differences and similarities between samples through the identifiable and indiscernible matrices are, respectively, computed. Then, a restoration method for missing feature values is proposed for use in the first stage. Second, to consider the nonlinear relationship among features, a neighborhood-based fuzzy similarity relationship between samples is investigated based on the Gaussian kernel function. By integrating the fuzzy similarity relationship matrix, label-specific feature matrix, and label correlation matrix, an objective function based on the regression model is presented, the optimal solutions to the label-specific feature and label correlation matrices based on the gradient descent strategy are provided, and a new multilabel classification method with missing labels is developed during the second stage. Finally, two-stage multilabel classification algorithms are designed. Experiments on 18 multilabel data sets demonstrate that our designed algorithms are effective not only for recovering missing feature values, but also for improving the classification performance of data with missing labels.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
jimi发布了新的文献求助10
3秒前
3秒前
3秒前
小左发布了新的文献求助10
3秒前
飞源发布了新的文献求助10
5秒前
5秒前
自觉向秋发布了新的文献求助10
8秒前
拉长的乐瑶完成签到,获得积分10
9秒前
xiaofeiyan发布了新的文献求助30
9秒前
FashionBoy应助称心元枫采纳,获得10
11秒前
李健应助全何荣采纳,获得10
14秒前
14秒前
111完成签到,获得积分10
15秒前
爱大美发布了新的文献求助10
15秒前
15秒前
15秒前
16秒前
17秒前
迷路的夏之完成签到,获得积分10
17秒前
乐乐应助hyr采纳,获得10
19秒前
小丫发布了新的文献求助10
19秒前
kaka发布了新的文献求助10
20秒前
不安分的橙子完成签到 ,获得积分10
21秒前
21秒前
谦让幻珊完成签到,获得积分10
21秒前
羊绮发布了新的文献求助10
22秒前
饶丹发布了新的文献求助10
24秒前
胡林完成签到,获得积分10
25秒前
26秒前
Chengcheng发布了新的文献求助10
27秒前
芯之痕发布了新的文献求助10
27秒前
自觉向秋发布了新的文献求助10
28秒前
29秒前
大秦完成签到,获得积分10
32秒前
fjiang2003发布了新的文献求助10
33秒前
土豆泥关注了科研通微信公众号
34秒前
小方发布了新的文献求助10
36秒前
liuxl完成签到,获得积分10
36秒前
袋鼠给袋鼠的求助进行了留言
37秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3976455
求助须知:如何正确求助?哪些是违规求助? 3520548
关于积分的说明 11203850
捐赠科研通 3257210
什么是DOI,文献DOI怎么找? 1798648
邀请新用户注册赠送积分活动 877835
科研通“疑难数据库(出版商)”最低求助积分说明 806539