Complementary ensemble clustering of biomedical data
نویسندگان
چکیده
منابع مشابه
A new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble
An ensemble clustering has been considered as one of the research approaches in data mining, pattern recognition, machine learning and artificial intelligence over the last decade. In clustering, the combination first produces several bases clustering, and then, for their aggregation, a function is used to create a final cluster that is as similar as possible to all the cluster bundles. The inp...
متن کاملEnsemble Non-negative Matrix Factorization for Clustering Biomedical Documents
Searching and mining biomedical literature database, such as MEDLINE, is the main source of generating scientific hypothesis for biomedical researchers. Through grouping similar documents together, clustering techniques can facilitate user’s need of effectively finding interested documents. Since non-negative matrix factorization (NMF) can effectively capture the latent semantic space with non-...
متن کاملthe clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance
با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
Weighted Ensemble Clustering for Increasing the Accuracy of the Final Clustering
Clustering algorithms are highly dependent on different factors such as the number of clusters, the specific clustering algorithm, and the used distance measure. Inspired from ensemble classification, one approach to reduce the effect of these factors on the final clustering is ensemble clustering. Since weighting the base classifiers has been a successful idea in ensemble classification, in th...
متن کاملClustering cancer gene expression data by projective clustering ensemble
Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Biomedical Informatics
سال: 2013
ISSN: 1532-0464
DOI: 10.1016/j.jbi.2013.02.001