Add to ORKG[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Drexel&SrcApp=hagerty_opac&KeyRecord=0162-1459&DestApp=JCR&RQ=IF_CAT_BOXPLO
In this paper we discuss and compare two clustering strategies: a hierarchical clustering and a dyn...
Abstract—In recent applications of clustering such as gene expression microarray analysis, collabora...
A functional clustering (FC) method, "k"-centres FC, for longitudinal data is proposed. The "k"-cent...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Ga...
[[abstract]]A correlation-based functional clustering method is proposed for grouping curves with si...
[[abstract]]This study considers two clustering criteria to achieve difierent goals of grouping simi...
[[abstract]]This study considers two clustering criteria to achieve different goals of grouping simi...
Functional data, where samples are random func-tions, are increasingly common and important in a var...
In machine learning, it is common to interpret each data sample as a multivariate vector disregardin...
In high dimensional data, clusters often only exist in ar-bitrarily oriented subspaces of the featur...
[[abstract]]A novel multivariate k-centers functional clustering algorithm for the multivariate func...
Clustering high dimensional data is an emerging research field. Subspace clustering or projected clu...
As a prolific research area in data mining, subspace clus-tering and related problems induced a vast...
[[abstract]]We propose a multivariate k-centers functional clustering algorithm for the multivariate...
Subspace clustering refers to the task of finding a multi-subspace representation that best fits a c...
In this paper we discuss and compare two clustering strategies: a hierarchical clustering and a dyn...
Abstract—In recent applications of clustering such as gene expression microarray analysis, collabora...
A functional clustering (FC) method, "k"-centres FC, for longitudinal data is proposed. The "k"-cent...
[[sponsorship]]統計科學研究所[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com/gateway/Ga...
[[abstract]]A correlation-based functional clustering method is proposed for grouping curves with si...
[[abstract]]This study considers two clustering criteria to achieve difierent goals of grouping simi...
[[abstract]]This study considers two clustering criteria to achieve different goals of grouping simi...
Functional data, where samples are random func-tions, are increasingly common and important in a var...
In machine learning, it is common to interpret each data sample as a multivariate vector disregardin...
In high dimensional data, clusters often only exist in ar-bitrarily oriented subspaces of the featur...
[[abstract]]A novel multivariate k-centers functional clustering algorithm for the multivariate func...
Clustering high dimensional data is an emerging research field. Subspace clustering or projected clu...
As a prolific research area in data mining, subspace clus-tering and related problems induced a vast...
[[abstract]]We propose a multivariate k-centers functional clustering algorithm for the multivariate...
Subspace clustering refers to the task of finding a multi-subspace representation that best fits a c...
In this paper we discuss and compare two clustering strategies: a hierarchical clustering and a dyn...
Abstract—In recent applications of clustering such as gene expression microarray analysis, collabora...
A functional clustering (FC) method, "k"-centres FC, for longitudinal data is proposed. The "k"-cent...