Jonathan Reynolds

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Jonathan Reynolds trusts overall

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

1. Pierre Geurts
2. Victor Francisco Rodriguez-Galiano

Papers from Jonathan Reynolds's perspective

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

1. Scikit-learn: Machine Learning in Python
2. Extremely randomized trees
3. Neural Network Ensembles
4. Machine learning predictive models for mineral prospectivity: an evaluation of neural networks, random forest, regression trees and support vector machines
5. Classification and regression trees
6. Bagging Predictors
7. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
8. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
9. A decision-theoretic generalization of on-line learning and an application to boosting
10. An Introduction to Variable and Feature Selection

Their papers

• Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees (2018) — 543 citations