Fernando Nogueira

Artificial Intelligence · with Aridas · 2016

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it; #10,614 of 35,345 by trust here, #19,873 by citations

Whom Fernando Nogueira trusts overall

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

1. Luís Torgo
2. Max Kuhn
3. Haibo He
4. Hui Han
5. Hien M. Nguyen
6. Michael R. Smith
7. Nitesh V. Chawla

Who trusts Fernando Nogueira overall

1. Tuong Le
2. Fabio Tanaka
3. Tarid Wongvorachan
4. Mateusz Buda
5. Felix Last
6. Sebastian Raschka
7. Roweida Mohammed
8. Abhik Jana

Papers from Fernando Nogueira's perspective

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

1. SMOTE: Synthetic Minority Over-sampling Technique
2. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
3. ADASYN: Adaptive synthetic sampling approach for imbalanced learning (IEEE World Congress on Computational Intelligence)
4. Learning from Imbalanced Data
5. The Condensed Nearest Neighbor Rule
6. Improving Identification of Difficult Small Classes by Balancing Class Distribution (Conference on Artificial Intelligence in Medicine in Europe)
7. on Knowledge and Data Engineering,
8. Scikit-learn: Machine Learning in Python
9. 10 Challenging Problems in Data Mining Research (International Journal of Information Technology and Decision Making)
10. The SHOGUN Machine Learning Toolbox

Their papers

• Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning (2016) — 2,559 citations