Rachel Harris

Information Fusion · 2004

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

Whom Rachel Harris trusts overall

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

  1. Leo Breiman
  2. John R. Koza
  3. Yoav Freund
  4. Prem Melville

Who trusts Rachel Harris overall

  1. Lior Rokach

Papers from Rachel Harris's perspective

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

  1. Bagging Predictors
  2. Neural Network Ensembles, Cross Validation, and Active Learning
  3. Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy
  4. Neural Network Ensembles
  5. Combining forecasts: A review and annotated bibliography
  6. Neural Networks and the Bias/Variance Dilemma
  7. Constructing Diverse Classifier Ensembles using Artificial Training Examples (International Joint Conference on Artificial Intelligence)
  8. Limits on the majority vote accuracy in classifier fusion (Pattern Analysis and Applications)
  9. Experiments with a New Boosting Algorithm
  10. A constructive algorithm for training cooperative neural network ensembles

Their papers