P. Yeh

IEEE Transactions on Knowledge and Data Engineering · with Wong · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom P. Yeh trusts overall

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

  1. Thomas G. Dietterich
  2. Leo Breiman
  3. Ron Kohavi

Papers from P. Yeh's perspective

Ordered by how strongly the researchers P. Yeh trusts endorse each paper. Same corpus, a different order for every researcher.

  1. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
  2. Heuristics of instability and stabilization in model selection
  3. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
  4. Data Mining Practical Machine Learning Tools and Techniques
  5. Study on the Impact of Partition-Induced Dataset Shift on $k$-Fold Cross-Validation (IEEE Transactions on Neural Networks and Learning Systems)
  6. Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap (Computational Statistics & Data Analysis)
  7. Data Mining: Practical Machine Learning Tools and Techniques, 3/E
  8. Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation (Pattern Recognition)
  9. Bagging Predictors
  10. The Nature of Statistical Learning Theory

Their papers