Maria Carolina Monard

Artificial Intelligence · 2002–2009

A researcher in the Science corpus: 6 papers; trusts 23 researchers and is trusted by 58 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it; #3,788 of 35,345 by trust here, #5,600 by citations
• Statistical Learning Theory — 10 citations into it
• Information Systems — 6 citations into it; #525 of 8,771 by trust here, #895 by citations
• Algorithms & Complexity — 5 citations into it

Whom Maria Carolina Monard trusts overall

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

1. J. Ross Quinlan
2. Subir Ghosh
3. Gustavo E. A. P. A. Batista
4. Nitesh V. Chawla
5. Peter Clark
6. Jorma Laurikkala
7. Pedro M. Domingos
8. Arthur P. Dempster
9. Cèsar Ferri
10. Gary M. Weiss

Who trusts Maria Carolina Monard overall

1. Alberto Fernández
2. Salvador Garcia
3. Victoria López
4. Francisco Herrera
5. Ronaldo Cristiano Prati
6. Gustavo E. A. P. A. Batista
7. Nitesh V. Chawla
8. Chumphol Bunkhumpornpat
9. Jason Poulos
10. Mikel Galar

Papers from Maria Carolina Monard's perspective

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

1. UCI Repository of machine learning databases
2. MetaCost: a general method for making classifiers cost-sensitive
3. The Foundations of Cost-Sensitive Learning
4. The use of the area under the ROC curve in the evaluation of machine learning algorithms
5. Learning and making decisions when costs and probabilities are both unknown (Knowledge Discovery and Data Mining)
6. The Condensed Nearest Neighbor Rule
7. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
8. C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
9. The CN2 Induction Algorithm
10. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction (Journal of Artificial Intelligence Research)

Their papers

• An analysis of four missing data treatment methods for supervised learning (2003) — 921 citations
• Data mining with imbalanced class distributions: concepts and methods (2009) — 67 citations
• Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior (2004) — 356 citations
• A study of the behavior of several methods for balancing machine learning training data (2004) — 4,104 citations
• Balancing Training Data for Automated Annotation of Keywords: a Case Study (2003) — 377 citations
• A Study of K-Nearest Neighbour as an Imputation Method (2002) — 480 citations