ArticleIEEE transactions on pattern analysis and machine intelligence2023
Transforming Complex Problems Into K-Means Solutions.
Article in IEEE transactions on pattern analysis and machine intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed.
- Label-free optical biomarker for prostate cancer diagnosis.Molecular medicine (Cambridge, Mass.) · 2026Article
- Machine learning-based precision subtyping and risk prediction in sepsis: a retrospective analysis using MIMIC-IV database.BMC infectious diseases · 2026Article
- Stratification of Pro-Atherogenic Phenotypes in Prediabetes Using Machine Learning.Biomedicines · 2026Article
- The Preferred Odor Characteristics of Cooked Medium-Milled Fragrant Simiao Rice.Foods (Basel, Switzerland) · 2026Article
- Single Mitochondrion Morphology-Function Relationship Analysis Using Fluorescent Probes and Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Analyzing Physician In Basket Burden and Efficiency Using K-Means Clustering.Applied clinical informatics · 2025Article
- Frailty in older adults patients: a prospective observational cohort study on subtype identification.European journal of medical research · 2025Observational
- Image Segmentation Based on the Optimized K-Means Algorithm with the Improved Hybrid Grey Wolf Optimization: Application in Ore Particle Size Detection.Sensors (Basel, Switzerland) · 2025Article
- E2F expression profiling-based subtypes in head and neck squamous cell carcinoma: clinical relevance, prognostic implications, and personalized therapy.World journal of surgical oncology · 2025Article
- Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology.Frontiers in pharmacology · 2025Article
- Association of exposure to multiple perfluoroalkyl and polyfluoroalkyl substances and glucose metabolism in National Health and Nutrition Examination Survey 2017-2018.Frontiers in public health · 2024Article
- Unsupervised cluster analysis of clinical and metabolite characteristics in patients with chronic complications of T2DM: an observational study of real data.Frontiers in endocrinology · 2023Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
K-means is a fundamental clustering algorithm widely used in both academic and industrial applications. Its popularity can be attributed to its simplicity and efficiency. Studies show the equivalence of K-means to principal component analysis, non-negative matrix factorization, and spectral clustering. However, these studies focus on standard K-means with squared euclidean distance. In this review paper, we unify the available approaches in generalizing K-means to solve challenging and complex problems. We show that these generalizations can be seen from four aspects: data representation, distance measure, label assignment, and centroid updating. As concrete applications of transforming problems into modified K-means formulation, we review the following applications: iterative subspace projection and clustering, consensus clustering, constrained clustering, domain adaptation, and outlier detection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.