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Imbalanced Data Classification Techniques

TopicLeading institutions, researchers & key papers

Imbalanced Data Classification Techniques is a topic indexed in PICO Portal from OpenAlex.

What is known about Imbalanced Data Classification Techniques?

PICO Portalrecord summary

This cluster of papers focuses on the challenges and techniques for handling imbalanced data in classification problems. It covers methods such as SMOTE, ROC analysis, cost-sensitive learning, ensemble methods, and their applications in fraud detection. The cluster also discusses the use of precision-recall and boosting algorithms, as well as the effectiveness of random forest in addressing imbalanced datasets.

How many works does Imbalanced Data Classification Techniques have?

PICO Portalindexed works

Imbalanced Data Classification Techniques has 97 works in the PICO Portal index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Imbalanced Data Classification Techniques?

PICO Portalopenalex

The OpenAlex for Imbalanced Data Classification Techniques is on the source record.

What are the most-cited papers on Imbalanced Data Classification Techniques?

PICO Portalmost cited works
Facing Imbalanced Data--Recommendations for the Use of Performance Metrics
László A. Jeni, Jeffrey F. Cohn, Fernando De la Torre
2013811 Citations
Credit Card Fraud Detection - Machine Learning methods
Dejan Varmedja, Mirjana Karanovic, Srdjan Sladojević, Marko Arsenović, Andraš Anderla
2019318 Citations
Intelligent financial fraud detection practices in post-pandemic era
Xiaoqian Zhu, Xiang Ao, Zidi Qin, Yanpeng Chang, Yang Liu, Qing He, Jianping Li
The Innovation. 2021190 CitationsOPEN ACCESS
A survey on statistical methods for health care fraud detection
Jing Li, Kuei-Ying Huang, Jionghua Jin, Jianjun Shi
Health Care Management Science. 2008172 Citations

Where is Imbalanced Data Classification Techniques research published, and who funds it?

PICO Portalvenues & funding sources

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock

How much of the research on Imbalanced Data Classification Techniques is open access?

PICO Portalopen access share
53%OPEN ACCESS
Gold
33%
Green
0%
Hybrid
13%
Bronze
7%
Closed
47%

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