Name
Abstract | ||
|---|---|---|
The rise of sophisticated machine learning models has brought accurate but obscure decision systems, which hide their logic, thus undermining transparency, trust, and the adoption of artificial intelligence (AI) in socially sensitive and safety-critical contexts. We introduce a local rule-based explanation method, providing faithful explanations of the decision made by a black box classifier on a ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MIS.2019.2957223 | IEEE Intelligent Systems |
Keywords | Field | DocType |
Genetic algorithms,Intelligent systems,Decision making,Decision trees,Machine learning algorithms,Prediction algorithms,Data models | Decision rule,Black box (phreaking),Data mining,Decision tree,Intelligent decision support system,Computer science,Counterfactual thinking,Counterfactual conditional,Artificial intelligence,Black box,Classifier (linguistics),Machine learning | Journal |
Volume | Issue | ISSN |
34 | 6 | 1541-1672 |
Citations | PageRank | References |
13 | 0.61 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Riccardo Guidotti | 1 | 112 | 24.81 |
| Anna Monreale | 2 | 581 | 42.49 |
| Fosca Giannotti | 3 | 2948 | 253.39 |
| Dino Pedreschi | 4 | 3083 | 244.47 |
| Salvatore Ruggieri | 5 | 518 | 68.63 |
| Franco Turini | 6 | 842 | 101.81 |