+ Site Statistics
+ Search Articles
+ Subscribe to Site Feeds
EurekaMag Most Shared ContentMost Shared
EurekaMag PDF Full Text ContentPDF Full Text
+ PDF Full Text
Request PDF Full TextRequest PDF Full Text
+ Follow Us
Follow on FacebookFollow on Facebook
Follow on TwitterFollow on Twitter
Follow on LinkedInFollow on LinkedIn

+ Translate

RAMOBoost: Ranked Minority Oversampling in Boosting

RAMOBoost: Ranked Minority Oversampling in Boosting

IEEE Transactions on Neural Networks 21(10): 1624-1642

In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imbalanced data. However, because of the complex characteristics of imbalanced data, many real-world solutions struggle to provide robust efficiency in learning-based applications. In an effort to address this problem, this paper presents Ranked Minority Oversampling in Boosting (RAMOBoost), which is a RAMO technique based on the idea of adaptive synthetic data generation in an ensemble learning system. Briefly, RAMOBoost adaptively ranks minority class instances at each learning iteration according to a sampling probability distribution that is based on the underlying data distribution, and can adaptively shift the decision boundary toward difficult-to-learn minority and majority class instances by using a hypothesis assessment procedure. Simulation analysis on 19 real-world datasets assessed over various metrics-including overall accuracy, precision, recall, F-measure, G-mean, and receiver operation characteristic analysis-is used to illustrate the effectiveness of this method.

(PDF emailed within 0-6 h: $19.90)

Accession: 055333087

Download citation: RISBibTeXText

PMID: 20805051

DOI: 10.1109/TNN.2010.2066988

Related references

Binarization With Boosting and Oversampling for Multiclass Classification. IEEE Transactions on Cybernetics 46(5): 1078-1091, 2015

Oversampling the Minority Class in the Feature Space. IEEE Transactions on Neural Networks and Learning Systems 27(9): 1947-1961, 2015

Improving lung cancer prognosis assessment by incorporating synthetic minority oversampling technique and score fusion method. Medical Physics 43(6): 2694-2694, 2016

Boosting minority student success. Creative Nursing 4(1): 12-12, 1998

Contract management. Boosting contracts to minority-owned firms. Hospitals & Health Networks 81(3): 18-18, 2007

Minority apprenticeship program--boosting agriculture and natural resources enrollments. NACTA journal 32(4): 16-18, 1988

Residency applicant screening procedures characteristics of pgy i ranked non ranked and non interviewed candidates. Anesthesiology (Hagerstown) 61(3 PART A): A458, 1984

Total knee arthroplasty outcomes in top-ranked and non-top-ranked orthopedic hospitals: an analysis of Medicare administrative data. Mayo Clinic Proceedings 87(4): 341-348, 2012

NIA supports minority investigators and research that addresses health disparities between minority and non-minority elderly populations. Science of Aging Knowledge Environment 2002(6): Vp1-Vp1, 2003

Goodness-of-fit testing for the inverse Gaussian distribution based on new entropy estimation using ranked set sampling and double ranked set sampling. Environmental Systems Research 1(1), 2012

On the mean character and variance of a ranked individual, and on the mean and variance of the intervals between ranked individuals Part II Case of certain skew curves. Biometrika 24(1-2): 203-279, 1932

On the mean character and variance of a ranked individual, and on the mean and variance of the intervals between ranked individuals Part I Symmetrical distributions. 1932

Median ranked set sampling with concomitant variables and a comparison with ranked set sampling and regression estimators. Environmetrics. 9(3): 255-267, E, 1998

Safety and immunogenicity of boosting BCG vaccinated subjects with BCG: comparison with boosting with a new TB vaccine, MVA85A. Plos One 4(6): E5934-E5934, 2009

On the Number of Ranked Species Trees Producing Anomalous Ranked Gene Trees. Ieee/Acm Transactions on Computational Biology and Bioinformatics 11(6): 1229-1238, 2016