Show-Jane Yen
Artificial Intelligence · 2009
A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 5 citations into it; #24,932 of 35,345 by trust here, #28,481 by citations
Whom Show-Jane Yen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Peter D. Turney
- Tian-Shyug Lee
- Nitesh V. Chawla
- Yoav Freund
- I-Fei Chen
- Charles Peter Elkan
- M. Maloof
- H. Sebastian Seung
- C. Drummond
- Taeho C. Jo
Who trusts Show-Jane Yen overall
Papers from Show-Jane Yen's perspective
Ordered by how strongly the researchers Show-Jane Yen trusts endorse each paper. Same corpus, a different order for every researcher.
- SMOTE: Synthetic Minority Over-sampling Technique
- C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
- C4.5 and Imbalanced Data sets: Investigating the eect of sampling method, probabilistic estimate, and decision tree structure
- Types of Cost in Inductive Concept Learning (arXiv.org)
- Class imbalances versus small disjuncts (SKDD)
- Learning When Data Sets are Imbalanced and When Costs are Unequal and Unknown
- The Foundations of Cost-Sensitive Learning
- SMOTEBoost: Improving Prediction of the Minority Class in Boosting
- Selective Sampling Using the Query by Committee Algorithm
- A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines (Expert systems with applications)
Their papers
- Cluster-based under-sampling approaches for imbalanced data distributions (2009) — 740 citations