Overview and Analysis of Contrast Pattern Based Classification
By Xiuzhen Zhang, Guozhu Dong. 2013
15 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing 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
- Octavio Loyola-González
- Raúl Monroy
- Dayton Hernández-Tamayo
- Milton García-Borroto
- J. A. Carrasco-Ochoa
- Armando López-Cuevas
- Javier Israel Mata-Sánchez
- Jorge Rodríguez
In Computer Vision and Pattern Recognition
In Industrial and Manufacturing Engineering
Citations in the corpus
- Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View (2019, background): “a items), each with the form: [fi # vj], where vj is a value in the domain of feature fi, and # is a relational operator from the set {∈, / ∈,=, 6=,≤, >} [7], [8], [135].”
- Contrast Pattern-Based Classification for Bot Detection on Twitter (2019, background): “classifiers provide a model that it is easy for a human to understand, and they have demonstrated to be more accurate than other popular classification models [15], [23].”
- A Pattern-Based Approach for Detecting Pneumatic Failures on Temporary Immersion Bioreactors (2019, background): “(iii) Contrast patterns are expressed in a language close to that used by human experts in the application domain [14,18].”