ORC: Ordered Rules for ClassificationA Discrete Optimization Approach to Associative Classification

By Dimitris J. Bertsimas, Allison Chang, Cynthia Rudin. 2012

15 citations recorded by the source corpus.

How researchers see this paper

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

1. Emilio Carrizosa
2. Dolores Romero Morales
3. Amaya Nogales-Gómez
4. Himabindu Lakkaraju
5. Sunny Dhamnani
6. Jure Leskovec
7. Cynthia Rudin
8. Berk Ustun

Citations in the corpus

• Interpretable Decision Sets: A Joint Framework for Description and Prediction (2016, background): “Learning decision lists has been particularly well studied [5, 38, 21] and has been successfully used for building small and interpretable models [3, 24].”
• Strongly agree or strongly disagree?: Rating features in Support Vector Machines (2016, methodology): “…popular approach has been to extract easy to understand structures from powerful yet black box type classi ers, such as if then rules, decision trees and decision tables (Baesens et al. 2003, Bertsimas et al. 2011, Martens et al. 2007, Martens and Provost 2013, Orsenigo and Vercellis 2003, 2004).”
• RAPID: Rapid and Precise Interpretable Decision Sets (2019, background): “This extends the areas of Decision Trees [18], [19] and Decision Lists [20], [21].”