R. Couronné

Artificial Intelligence · 2018

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

Subfields

Whom R. Couronné trusts overall

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

  1. Anne-Laure Boulesteix
  2. Andy Liaw
  3. Bernd Bischl
  4. Philipp Probst
  5. Matthew C. Wiener
  6. Michel Lang
  7. Leo Breiman

Papers from R. Couronné's perspective

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

  1. mlr: Machine Learning in R
  2. Classification and Regression by randomForest
  3. Tunability: Importance of Hyperparameters of Machine Learning Algorithms
  4. A Plea for Neutral Comparison Studies in Computational Sciences
  5. Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research
  6. ArrayExpress—a public repository for microarray gene expression data at the EBI (Nucleic Acids Res.)
  7. Hyperparameters and tuning strategies for random forest (WIREs Data Mining Knowl. Discov.)
  8. Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics (WIREs Data Mining Knowl. Discov.)
  9. To tune or not to tune the number of trees in random forest?
  10. The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Their papers