Study of the impact of resampling methods for contrast pattern based classifiers in imbalanced databases

By Octavio Loyola-González, José Francisco Martínez Trinidad, J. A. Carrasco-Ochoa, Milton García-Borroto. 2016

173 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Octavio Loyola-González
2. Raúl Monroy
3. Dayton Hernández-Tamayo
4. Milton García-Borroto
5. J. A. Carrasco-Ochoa
6. Armando López-Cuevas
7. Javier Israel Mata-Sánchez
8. Jorge Rodríguez

In Electrical and Electronic Engineering

1. Octavio Loyola-González
2. Raúl Monroy
3. Milton García-Borroto
4. J. A. Carrasco-Ochoa
5. José Francisco Martínez Trinidad

Citations in the corpus

• Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View (2019, background): “A pattern is an expression defined in a certain language that describes a collection of objects [7], [8], [100], [110], [133], [134].”
• Detecting Pneumatic Failures on Temporary Immersion Bioreactors (2016, methodology): “These classifiers have been used to solve realworld problems in fields like bioinformatics [9], intruder detection [5], anomaly detection in network connection data [29], rare event forecasting [27], and privacy preserving data mining [1], which are well-known class imbalance problems [20,22].”
• Contrast Pattern-Based Classification for Bot Detection on Twitter (2019, methodology): “There are many contrast pattern-based classifiers reported on in the literature [18], [23], [54], [55].”