V. Segtnan

2004–2013

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom V. Segtnan trusts overall

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

1. Leo Breiman
2. Eric Bauer
3. Trevor J. Hastie
4. Hyun-Chul Kim

Who trusts V. Segtnan overall

1. Tormod Næs

Papers from V. Segtnan's perspective

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

1. Bagging Predictors
2. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
3. Heuristics of instability and stabilization in model selection
4. Random Forests
5. Stacked regressions
6. Constructing support vector machine ensemble (Pattern Recognition)
7. Boosting the margin: A new explanation for the effectiveness of voting methods
8. The Nature of Statistical Learning Theory
9. Shape Quantization and Recognition with Randomized Trees
10. Arcing classifier (with discussion and a rejoinder by the author)

Their papers

• Multi-block regression based on combinations of orthogonalisation, PLS-regression and canonical correlation analysis (2013) — 77 citations
• A comparison of methods for analysing regression models with both spectral and designed variables (2004) — 54 citations
• Ensemble methods and partial least squares regression (2004) — 84 citations