Hong Han

2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS) · 2016

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Hong Han trusts overall

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

  1. Robin Genuer
  2. Trevor J. Hastie
  3. Leo Breiman
  4. Jean‐Michel Poggi

Papers from Hong Han's perspective

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

  1. Random Forests
  2. Variable selection using random forests
  3. Bagging Predictors
  4. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization
  5. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  6. 双対平坦空間におけるLeast Angle Regressionと情報量規準
  7. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
  8. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
  9. A decision-theoretic generalization of on-line learning and an application to boosting
  10. Consistency of Random Forests and Other Averaging Classifiers

Their papers