Techniques for Extracting Classification and Regression Rules from Artificial Neural Networks
By David B. Fogel, Charles J. Robinson. 2003
15 citations recorded by the source corpus.
Subfields: Artificial Intelligence
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
- Sérgio Moro
- Paulo Rita
- Mark J. Embrechts
- Paulo Cortez
- Mohammed Berrada
- Amina Adadi
- Vaishak Belle
- Ioannis Papantonis
Citations in the corpus
- Opening black box Data Mining models using Sensitivity Analysis (2011, background): “The extraction of rules is the most popular solution [7][8][9].”
- A data-driven approach to predict the success of bank telemarketing (2014, background): “By analyzing the sensitivity responses, it is possible to measure input relevance and average impact of a particular input in the model.”
- Mortality assessment in intensive care units via adverse events using artificial neural networks (2006, background): “The extraction of knowledge from ANNs is still an active research area [23].”