Accelerating Infinite Ensemble of Clustering by Pivot Features
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DOI: 10.1007/s12559-018-9583-8
Abstract: The infinite ensemble clustering (IEC) incorporates both ensemble clustering and representation learning by fusing infinite basic partitions and shows appealing performance in the unsupervised context. However, it needs to solve the linear equation system with… read more here.
Keywords: accelerating infinite; pivot features; clustering pivot; ensemble clustering ... See more keywords
Ensemble clustering based on dense representation
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DOI: 10.1016/j.neucom.2019.04.078
Abstract: Abstract Ensemble clustering has emerged as a powerful tool for improving the stability and accuracy of the clustering task. Although various approaches have been proposed for improving the performance of algorithms, most of them ignored… read more here.
Keywords: method; based dense; clustering based; dense representation ... See more keywords
scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering
Sign Up to like & getrecommendations! Published in 2023 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btad075
Abstract: Abstract Motivation Single-cell RNA sequencing (scRNA-seq) is an increasingly popular technique for transcriptomic analysis of gene expression at the single-cell level. Cell-type clustering is the first crucial task in the analysis of scRNA-seq data that… read more here.
Keywords: cell; autoencoder; scrna seq; analysis ... See more keywords
Stratified Feature Sampling for Semi-Supervised Ensemble Clustering
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DOI: 10.1109/access.2019.2939581
Abstract: Ensemble Clustering (EC), which seeks to generate a consensus clustering by integrating multiple base clusterings, has attracted increasing attentions. However, traditional EC methods typically have three main limitations: (1) High dimensional data present a huge… read more here.
Keywords: stratified feature; semi supervised; supervised ensemble; ensemble clustering ... See more keywords
Did They Sense it Coming? A Pipelined Approach for Tsunami Prediction Based on Aquatic Behavior Using Ensemble Clustering and Fuzzy Rule-Based Classification
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DOI: 10.1109/access.2020.3022865
Abstract: Tsunami is one of the real feelings of dread among humanity. Designing an early and effective Tsunami Warning System (TWS) is an immediate goal, for which the scientific community is working. Underwater seismic responses sensed… read more here.
Keywords: tsunami; sense coming; approach; coming pipelined ... See more keywords
An Unsupervised Ensemble Clustering Approach for the Analysis of Student Behavioral Patterns
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DOI: 10.1109/access.2021.3049157
Abstract: Specialized services and management must understand students’ behavioral patterns in a timely and accurate manner. Based on these patterns, we can make targeted rules, especially for unexpected patterns. To perform this type of work, a… read more here.
Keywords: student behavioral; analysis; ensemble clustering; student ... See more keywords
Double weighted ensemble clustering for cancer subtypes analysis
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DOI: 10.1109/access.2022.3167031
Abstract: The era of big data provides the possibility of precision medicine. The most important idea we have for cancer is to divide and treat. Theoretically, each person’s cancer should be different, so it is very… read more here.
Keywords: weighted ensemble; cancer; double weighted; analysis ... See more keywords
Soft Subspace Based Ensemble Clustering for Multivariate Time Series Data.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3146136
Abstract: Recently, multivariate time series (MTS) clustering has gained lots of attention. However, state-of-the-art algorithms suffer from two major issues. First, few existing studies consider correlations and redundancies between variables of MTS data. Second, since different… read more here.
Keywords: soft subspace; multivariate time; time series; ensemble clustering ... See more keywords
Enhanced Ensemble Clustering via Fast Propagation of Cluster-Wise Similarities
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2018.2876202
Abstract: Ensemble clustering has been a popular research topic in data mining and machine learning. Despite its significant progress in recent years, there are still two challenging issues in the current ensemble clustering research. First, most… read more here.
Keywords: wise; cluster wise; propagation cluster; ensemble clustering ... See more keywords
Divergence-Based Locally Weighted Ensemble Clustering with Dictionary Learning and L2,1-Norm
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DOI: 10.3390/e24101324
Abstract: Accurate clustering is a challenging task with unlabeled data. Ensemble clustering aims to combine sets of base clusterings to obtain a better and more stable clustering and has shown its ability to improve clustering accuracy.… read more here.
Keywords: weighted ensemble; divergence based; based locally; ensemble clustering ... See more keywords
Ensemble Clustering via Co-association Matrix Self-enhancement
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DOI: 10.48550/arxiv.2205.05937
Abstract: Ensemble clustering integrates a set of base clustering results to generate a stronger one. Existing methods usually rely on a co-association (CA) matrix that measures how many times two samples are grouped into the same… read more here.
Keywords: matrix; association matrix; self enhancement; ensemble clustering ... See more keywords