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A Survey of Methods for Explaining Black Box Models
- Riccardo Guidotti, A. Monreale, F. Turini, D. Pedreschi, F. Giannotti
- Computer ScienceACM Comput. Surv.
- 6 February 2018
A classification of the main problems addressed in the literature with respect to the notion of explanation and the type of black box system is provided to help the researcher to find the proposals more useful for his own work.
Trajectory pattern mining
This paper develops an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects and introduces trajectory patterns as concise descriptions of frequent behaviours in terms of both space and time.
Human mobility, social ties, and link prediction
- Dashun Wang, D. Pedreschi, Chaoming Song, F. Giannotti, A. Barabasi
- Computer ScienceKDD
- 21 August 2011
It is shown that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures, and the prediction accuracy can be significantly improved by learning a supervised classifier based on combined mobility and network measures.
Discrimination-aware data mining
This approach leads to a precise formulation of the redlining problem along with a formal result relating discriminatory rules with apparently safe ones by means of background knowledge, and an empirical assessment of the results on the German credit dataset.
DEMON: a local-first discovery method for overlapping communities
A simple local-first approach to community discovery, able to unveil the modular organization of real complex networks, by democratically letting each node vote for the communities it sees surrounding it in its limited view of the global system.
Time-focused clustering of trajectories of moving objects
This paper proposes an adaptation of a density-based clustering algorithm to trajectory data based on a simple notion of distance between trajectories, with the aim of exploiting the intrinsic semantics of the temporal dimension to improve the quality of trajectory clustering.
Local Rule-Based Explanations of Black Box Decision Systems
- Riccardo Guidotti, A. Monreale, S. Ruggieri, D. Pedreschi, F. Turini, F. Giannotti
- Computer ScienceArXiv
- 28 May 2018
This paper proposes LORE, an agnostic method able to provide interpretable and faithful explanations for black box outcome explanation, and shows that LORE outperforms existing methods and baselines both in the quality of explanations and in the accuracy in mimicking the black box.
Reasoning about Termination of Pure Prolog Programs
It is proved that various ways of defining semantics coincide for acceptable general programs as well as under the assumption of non-floundering from ground goals every left terminating general program is acceptable.
Returners and explorers dichotomy in human mobility
- L. Pappalardo, F. Simini, S. Rinzivillo, D. Pedreschi, F. Giannotti, A. Barabasi
- BiologyNature communications
- 8 September 2015
It is shown that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.
Data mining for discrimination discovery
This article formalizes the processes of direct and indirect discrimination discovery by modelling protected-by-law groups and contexts where discrimination occurs in a classification rule based syntax and proposes two inference models and provides automatic procedures for their implementation.