Michael I. Miller

Artificial Intelligence · with Ip · 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

• Artificial Intelligence — 7 citations into it
• Molecular Biology — 5 citations into it

Whom Michael I. Miller trusts overall

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

1. Max Kuhn
2. Houtao Deng
3. Robin Genuer
4. André Altmann

Papers from Michael I. Miller's perspective

Ordered by how strongly the researchers Michael I. Miller 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

• A Comparison of Random Forest Variable Selection Methods for Classification Prediction Modeling (2019) — 1,354 citations