Sara del Río

Artificial Intelligence · 2014

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Sara del Río trusts overall

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

  1. Jorma Laurikkala
  2. Muthu Dayalan
  3. Niko Speybroeck
  4. Chao Chen
  5. Salvador Garcia
  6. Gustavo E. A. P. A. Batista
  7. Nitesh V. Chawla
  8. Chumphol Bunkhumpornpat
  9. Hui Han
  10. Victoria López

Who trusts Sara del Río overall

  1. Bartosz Krawczyk
  2. Alberto Fernández
  3. Joffrey L. Leevy
  4. Antoine Jean-Pierre Tixier
  5. Robin Genuer
  6. Salvador Garcia
  7. Taghi M. Khoshgoftaar
  8. Matthew R. Hallowell
  9. Jean‐Michel Poggi

Papers from Sara del Río's perspective

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

  1. SMOTE: Synthetic Minority Over-sampling Technique
  2. Learning and making decisions when costs and probabilities are both unknown (Knowledge Discovery and Data Mining)
  3. MetaCost: a general method for making classifiers cost-sensitive
  4. A study of the behavior of several methods for balancing machine learning training data
  5. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
  6. The Foundations of Cost-Sensitive Learning
  7. Cost-sensitive learning by cost-proportionate example weighting
  8. The class imbalance problem: A systematic study
  9. MapReduce: simplified data processing on large clusters
  10. Classification and regression trees

Their papers