Vincent Cheng-Siong Lee

Artificial Intelligence · with Phua · 2004–2010

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Vincent Cheng-Siong Lee trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. David Hilton Wolpert
  2. M. Maloof
  3. Graham J. Williams
  4. Simon Hawkins
  5. Nathalie Japkowicz
  6. C. Drummond
  7. Ludmila I. Kuncheva
  8. Saso Dzeroski
  9. Pedro M. Domingos
  10. Nitesh V. Chawla

Who trusts Vincent Cheng-Siong Lee overall

  1. Yuxi Li
  2. Leman Akoglu
  3. Charu C. Aggarwal
  4. Johan L. Perols
  5. Andrea Dal Pozzolo
  6. Hanghang Tong
  7. David Savage

Papers from Vincent Cheng-Siong Lee's perspective

Ordered by how strongly the researchers Vincent Cheng-Siong Lee trusts endorse each paper. Same corpus, a different order for every researcher.

  1. MetaCost: a general method for making classifiers cost-sensitive
  2. SMOTE: Synthetic Minority Over-sampling Technique
  3. Original Contribution: Stacked generalization
  4. C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
  5. Outlier Detection Using Replicator Neural Networks (International Conference on Data Warehousing and Knowledge Discovery)
  6. Data Mining - Concepts and Techniques (Künstliche Intell.)
  7. Mining concept-drifting data streams using ensemble classifiers
  8. Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection
  9. The class imbalance problem: A systematic study
  10. No free lunch theorems for optimization

Their papers