Jaime Lynn Speiser

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jaime Lynn Speiser trusts overall

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

  1. Max Kuhn
  2. Houtao Deng
  3. Robin Genuer
  4. André Altmann
  5. Giuseppe Casalicchio
  6. George C. Runger
  7. Jean‐Michel Poggi
  8. Laura Tolosi
  9. M. L. N. L. Nelson Sanchez-Pinto
  10. Leo Breiman

Papers from Jaime Lynn Speiser's perspective

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

  1. Random Forests
  2. Gene selection with guided regularized random forest
  3. Permutation importance: a corrected feature importance measure
  4. Evaluation of variable selection methods for random forests and omics data sets (Briefings Bioinform.)
  5. OpenML: An R package to connect to the machine learning platform OpenML
  6. The caret Package
  7. Comparison of Variable Selection Methods for Clinical Predictive Modeling
  8. VSURF: An R Package for Variable Selection Using Random Forests (The R Journal)
  9. An Introduction to Variable and Feature Selection
  10. Classification and Regression by randomForest

Their papers