J. Blackard

Nature and Landscape Conservation · 1999–2006

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Nature and Landscape Conservation — 9 citations into it; #4,165 of 6,941 by trust here, #3,783 by citations
• Ecological Modeling — 8 citations into it; #1,506 of 2,530 by trust here, #1,430 by citations

Whom J. Blackard trusts overall

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

1. John A. Hertz
2. Anders Krogh
3. David E. Rumelhart
4. Michael P. Austin
5. B. D. Ripley
6. Leo Breiman

Who trusts J. Blackard overall

1. Soham De
2. Aaron Klein
3. Xinru Wang
4. Yinjun Wu
5. Avleen Singh Bijral
6. Dallas Card
7. Valentina Zantedeschi
8. Abhay Kumar Yadav
9. Antonio A. Ginart
10. Stefan Falkner

Papers from J. Blackard's perspective

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

1. Experiments with a New Boosting Algorithm
2. Introduction to the theory of neural computation
3. Bagging Predictors
4. Neural Networks for Pattern Recognition
5. Greedy function approximation: A gradient boosting machine.
6. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling
7. Comparing five modelling techniques for predicting forest characteristics
8. Stochastic gradient boosting
9. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
10. Learning internal representations by error propagation

Their papers

• Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods (2006) — 299 citations
• Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables (1999)