Hanne H. F. Refsgaard

Artificial Intelligence · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Hanne H. F. Refsgaard trusts overall

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

  1. Jerome H. Friedman
  2. Andy Liaw
  3. Paulo Cortez
  4. Anna Palczewska
  5. Torsten Hothorn
  6. V. Kuz'min
  7. Raphaël Marée

Who trusts Hanne H. F. Refsgaard overall

  1. Amina Adadi

Papers from Hanne H. F. Refsgaard's perspective

Ordered by how strongly the researchers Hanne H. F. Refsgaard trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Random Forests
  2. Classification and Regression by randomForest
  3. Greedy function approximation: A gradient boosting machine.
  4. Scikit-learn: Machine Learning in Python
  5. Unbiased Recursive Partitioning: A Conditional Inference Framework
  6. Using sensitivity analysis and visualization techniques to open black box data mining models
  7. ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
  8. Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
  9. Random Forest Models To Predict Aqueous Solubility
  10. Interpreting random forest classification models using a feature contribution method

Their papers