发布求助
文献互助 智能选刊 最新文献

Journal of Classification最新文献

筛选
英文 中文
Clustered Sparse Structural Equation Modeling for Heterogeneous Data 异构数据的聚类稀疏结构方程建模
IF 2 4区 计算机科学
Journal of Classification Pub Date : 2023-11-30 DOI: 10.1007/s00357-023-09449-9
Ippei Takasawa, Kensuke Tanioka, Hiroshi Yadohisa
{"title":"Clustered Sparse Structural Equation Modeling for Heterogeneous Data","authors":"Ippei Takasawa, Kensuke Tanioka, Hiroshi Yadohisa","doi":"10.1007/s00357-023-09449-9","DOIUrl":"https://doi.org/10.1007/s00357-023-09449-9","url":null,"abstract":"<p>Joint analysis with clustering and structural equation modeling is one of the most popular approaches to analyzing heterogeneous data. The methods involved in this approach estimate a path diagram of the same shape for each cluster and interpret the clusters according to the magnitude of the coefficients. However, these methods have problems with difficulty in interpreting the coefficients when the number of clusters and/or paths increases and are unable to deal with any situation where the path diagram for each cluster is different. To tackle these problems, we propose two methods for simplifying the path structure and facilitating interpretation by estimating a different form of path diagram for each cluster using sparse estimation. The proposed methods and related methods are compared using numerical simulation and real data examples. The proposed methods are superior to the existing methods in terms of both fitting and interpretation.</p>","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"199 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138535995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Classification Under Partial Reject Options 分类在部分拒绝选项下
IF 2 4区 计算机科学
Journal of Classification Pub Date : 2023-11-25 DOI: 10.1007/s00357-023-09455-x
Måns Karlsson, Ola Hössjer
{"title":"Classification Under Partial Reject Options","authors":"Måns Karlsson, Ola Hössjer","doi":"10.1007/s00357-023-09455-x","DOIUrl":"https://doi.org/10.1007/s00357-023-09455-x","url":null,"abstract":"<p>In many applications there is ambiguity about which (if any) of a finite number <i>N</i> of hypotheses that best fits an observation. It is of interest then to possibly output a whole set of categories, that is, a scenario where the size of the classified set of categories ranges from 0 to <i>N</i>. Empty sets correspond to an outlier, sets of size 1 represent a firm decision that singles out one hypothesis, sets of size <i>N</i> correspond to a rejection to classify, whereas sets of sizes <span>(2,ldots ,N-1)</span> represent a partial rejection to classify, where some hypotheses are excluded from further analysis. In this paper, we review and unify several proposed methods of Bayesian set-valued classification, where the objective is to find the optimal Bayesian classifier that maximizes the expected reward. We study a large class of reward functions with rewards for sets that include the true category, whereas additive or multiplicative penalties are incurred for sets depending on their size. For models with one homogeneous block of hypotheses, we provide general expressions for the accompanying Bayesian classifier, several of which extend previous results in the literature. Then, we derive novel results for the more general setting when hypotheses are partitioned into blocks, where ambiguity within and between blocks are of different severity. We also discuss how well-known methods of classification, such as conformal prediction, indifference zones, and hierarchical classification, fit into our framework. Finally, set-valued classification is illustrated using an ornithological data set, with taxa partitioned into blocks and parameters estimated using MCMC. The associated reward function’s tuning parameters are chosen through cross-validation.</p>","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"29 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138536017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Model-Based Clustering with Nested Gaussian Clusters 基于模型的嵌套高斯聚类
4区 计算机科学
Journal of Classification Pub Date : 2023-11-13 DOI: 10.1007/s00357-023-09453-z
Jason Hou-Liu, Ryan P. Browne
{"title":"Model-Based Clustering with Nested Gaussian Clusters","authors":"Jason Hou-Liu, Ryan P. Browne","doi":"10.1007/s00357-023-09453-z","DOIUrl":"https://doi.org/10.1007/s00357-023-09453-z","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"75 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136346468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data 聚类微生物组数据的Logistic正态多项式因子分析
4区 计算机科学
Journal of Classification Pub Date : 2023-11-07 DOI: 10.1007/s00357-023-09452-0
Wangshu Tu, Sanjeena Subedi
{"title":"Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data","authors":"Wangshu Tu, Sanjeena Subedi","doi":"10.1007/s00357-023-09452-0","DOIUrl":"https://doi.org/10.1007/s00357-023-09452-0","url":null,"abstract":"The human microbiome plays an important role in human health and disease status. Next-generating sequencing technologies allow for quantifying the composition of the human microbiome. Clustering these microbiome data can provide valuable information by identifying underlying patterns across samples. Recently, Fang and Subedi (2023) proposed a logistic normal multinomial mixture model (LNM-MM) for clustering microbiome data. As microbiome data tends to be high dimensional, here, we develop a family of logistic normal multinomial factor analyzers (LNM-FA) by incorporating a factor analyzer structure in the LNM-MM. This family of models is more suitable for high-dimensional data as the number of free parameters in LNM-FA can be greatly reduced by assuming that the number of latent factors is small. Parameter estimation is done using a computationally efficient variant of the alternating expectation conditional maximization algorithm that utilizes variational Gaussian approximations. The proposed method is illustrated using simulated and real datasets.","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135431080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Editorial: Journal of Classification Vol. 40-3 社论：分类学杂志》第 40-3 卷
IF 2 4区 计算机科学
Journal of Classification Pub Date : 2023-11-01 DOI: 10.1007/s00357-023-09454-y
P. McNicholas
{"title":"Editorial: Journal of Classification Vol. 40-3","authors":"P. McNicholas","doi":"10.1007/s00357-023-09454-y","DOIUrl":"https://doi.org/10.1007/s00357-023-09454-y","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"42 1","pages":"467 - 467"},"PeriodicalIF":2.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139292880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Missing Values and Directional Outlier Detection in Model-Based Clustering 基于模型聚类的缺失值和定向离群点检测
4区 计算机科学
Journal of Classification Pub Date : 2023-10-31 DOI: 10.1007/s00357-023-09450-2
Hung Tong, Cristina Tortora
{"title":"Missing Values and Directional Outlier Detection in Model-Based Clustering","authors":"Hung Tong, Cristina Tortora","doi":"10.1007/s00357-023-09450-2","DOIUrl":"https://doi.org/10.1007/s00357-023-09450-2","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"48 88","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135863281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multiclass Sparse Discriminant Analysis Incorporating Graphical Structure Among Predictors 多类稀疏判别分析
4区 计算机科学
Journal of Classification Pub Date : 2023-10-14 DOI: 10.1007/s00357-023-09451-1
Jingxuan Luo, Xuejiao Li, Chongxiu Yu, Gaorong Li
{"title":"Multiclass Sparse Discriminant Analysis Incorporating Graphical Structure Among Predictors","authors":"Jingxuan Luo, Xuejiao Li, Chongxiu Yu, Gaorong Li","doi":"10.1007/s00357-023-09451-1","DOIUrl":"https://doi.org/10.1007/s00357-023-09451-1","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimal Band Selection Using Evolutionary Machine Learning to Improve the Accuracy of Hyper-spectral Images Classification: a Novel Migration-Based Particle Swarm Optimization 利用进化机器学习优化波段选择提高高光谱图像分类精度:一种新的基于迁移的粒子群优化方法
4区 计算机科学
Journal of Classification Pub Date : 2023-09-16 DOI: 10.1007/s00357-023-09448-w
Milad Vahidi, Sina Aghakhani, Diego Martín, Hossein Aminzadeh, Mehrdad Kaveh
{"title":"Optimal Band Selection Using Evolutionary Machine Learning to Improve the Accuracy of Hyper-spectral Images Classification: a Novel Migration-Based Particle Swarm Optimization","authors":"Milad Vahidi, Sina Aghakhani, Diego Martín, Hossein Aminzadeh, Mehrdad Kaveh","doi":"10.1007/s00357-023-09448-w","DOIUrl":"https://doi.org/10.1007/s00357-023-09448-w","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135308373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On Model-Based Clustering of Directional Data with Heavy Tails 基于模型的重尾定向数据聚类研究
4区 计算机科学
Journal of Classification Pub Date : 2023-09-12 DOI: 10.1007/s00357-023-09445-z
Yingying Zhang, Volodymyr Melnykov, Igor Melnykov
{"title":"On Model-Based Clustering of Directional Data with Heavy Tails","authors":"Yingying Zhang, Volodymyr Melnykov, Igor Melnykov","doi":"10.1007/s00357-023-09445-z","DOIUrl":"https://doi.org/10.1007/s00357-023-09445-z","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135830983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Expanding the Class of Global Objective Functions for Dissimilarity-Based Hierarchical Clustering 基于不相似度的层次聚类的全局目标函数类扩展
4区 计算机科学
Journal of Classification Pub Date : 2023-09-04 DOI: 10.1007/s00357-023-09447-x
Sebastien Roch
{"title":"Expanding the Class of Global Objective Functions for Dissimilarity-Based Hierarchical Clustering","authors":"Sebastien Roch","doi":"10.1007/s00357-023-09447-x","DOIUrl":"https://doi.org/10.1007/s00357-023-09447-x","url":null,"abstract":"","PeriodicalId":50241,"journal":{"name":"Journal of Classification","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135403856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信