Interpretable and Reliable Rule Classification Based on Conformal Prediction

H. Abdelqader; E. Smirnov; M. Pont; M. Geijselaers

doi:10.1007/978-3-031-23618-1_26

Interpretable and Reliable Rule Classification Based on Conformal Prediction

H. Abdelqader^*, E. Smirnov, M. Pont, M. Geijselaers

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

This paper deals with the challenging problem of simultaneously integrating interpretablility and reliability into prediction models in machine learning. It proposes to combine the interpretable models of decision rules with the reliable models based on conformal prediction. The result is a new technique of conformal decision rules. Given a test instance, the technique is capable of providing a point prediction, an explanation, and a confidence value for that prediction plus a prediction set. The experiments show when and how conformal decision rules can be used for interpretable and reliable machine learning.

Original language	English
Title of host publication	Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings
Editors	Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana, Konstantinos Sechidis, Arif Canakoglu, Sara Pido, Pietro Pinoli, Albert Bifet, Sepideh Pashami
Publisher	Springer International Publishing AG
Pages	385-401
Number of pages	17
Volume	1752
ISBN (Electronic)	978-3-031-23618-1
ISBN (Print)	9783031236174
DOIs	https://doi.org/10.1007/978-3-031-23618-1_26
Publication status	Published - 2023
Event	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) - Grenoble, France Duration: 19 Sept 2022 → 23 Sept 2022 https://2022.ecmlpkdd.org/

Publication series

Series	Communications in Computer and Information Science
Volume	1752
ISSN	1865-0929

Conference

Conference	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
Abbreviated title	ECML PKDD 2022
Country/Territory	France
City	Grenoble
Period	19/09/22 → 23/09/22
Internet address	https://2022.ecmlpkdd.org/

Keywords

Interpretable machine learning
Reliable machine learning
Decision rules
Conformal prediction

Access to Document

10.1007/978-3-031-23618-1_26

Cite this

Abdelqader, H., Smirnov, E., Pont, M., & Geijselaers, M. (2023). Interpretable and Reliable Rule Classification Based on Conformal Prediction. In I. Koprinska, P. Mignone, R. Guidotti, S. Jaroszewicz, H. Fröning, F. Gullo, P. M. Ferreira, D. Roqueiro, G. Ceddia, S. Nowaczyk, J. Gama, R. Ribeiro, R. Gavaldà, E. Masciari, Z. Ras, E. Ritacco, F. Naretto, A. Theissler, P. Biecek, W. Verbeke, G. Schiele, F. Pernkopf, M. Blott, I. Bordino, I. L. Danesi, G. Ponti, L. Severini, A. Appice, G. Andresini, I. Medeiros, G. Graça, L. Cooper, N. Ghazaleh, J. Richiardi, D. Saldana, K. Sechidis, A. Canakoglu, S. Pido, P. Pinoli, A. Bifet, ... S. Pashami (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings (Vol. 1752, pp. 385-401). Springer International Publishing AG. https://doi.org/10.1007/978-3-031-23618-1_26

Abdelqader, H. ; Smirnov, E. ; Pont, M. et al. / Interpretable and Reliable Rule Classification Based on Conformal Prediction. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings. editor / Irena Koprinska ; Paolo Mignone ; Riccardo Guidotti ; Szymon Jaroszewicz ; Holger Fröning ; Francesco Gullo ; Pedro M. Ferreira ; Damian Roqueiro ; Gaia Ceddia ; Slawomir Nowaczyk ; João Gama ; Rita Ribeiro ; Ricard Gavaldà ; Elio Masciari ; Zbigniew Ras ; Ettore Ritacco ; Francesca Naretto ; Andreas Theissler ; Przemyslaw Biecek ; Wouter Verbeke ; Gregor Schiele ; Franz Pernkopf ; Michaela Blott ; Ilaria Bordino ; Ivan Luciano Danesi ; Giovanni Ponti ; Lorenzo Severini ; Annalisa Appice ; Giuseppina Andresini ; Ibéria Medeiros ; Guilherme Graça ; Lee Cooper ; Naghmeh Ghazaleh ; Jonas Richiardi ; Diego Saldana ; Konstantinos Sechidis ; Arif Canakoglu ; Sara Pido ; Pietro Pinoli ; Albert Bifet ; Sepideh Pashami. Vol. 1752 Springer International Publishing AG, 2023. pp. 385-401 (Communications in Computer and Information Science, Vol. 1752).

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title = "Interpretable and Reliable Rule Classification Based on Conformal Prediction",

abstract = "This paper deals with the challenging problem of simultaneously integrating interpretablility and reliability into prediction models in machine learning. It proposes to combine the interpretable models of decision rules with the reliable models based on conformal prediction. The result is a new technique of conformal decision rules. Given a test instance, the technique is capable of providing a point prediction, an explanation, and a confidence value for that prediction plus a prediction set. The experiments show when and how conformal decision rules can be used for interpretable and reliable machine learning.",

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author = "H. Abdelqader and E. Smirnov and M. Pont and M. Geijselaers",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), ECML PKDD 2022 ; Conference date: 19-09-2022 Through 23-09-2022",

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doi = "10.1007/978-3-031-23618-1_26",

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editor = "Irena Koprinska and Paolo Mignone and Riccardo Guidotti and Szymon Jaroszewicz and Holger Fr{\"o}ning and Francesco Gullo and Ferreira, {Pedro M.} and Damian Roqueiro and Gaia Ceddia and Slawomir Nowaczyk and Jo{\~a}o Gama and Rita Ribeiro and Ricard Gavald{\`a} and Elio Masciari and Zbigniew Ras and Ettore Ritacco and Francesca Naretto and Andreas Theissler and Przemyslaw Biecek and Wouter Verbeke and Gregor Schiele and Franz Pernkopf and Michaela Blott and Ilaria Bordino and Danesi, {Ivan Luciano} and Giovanni Ponti and Lorenzo Severini and Annalisa Appice and Giuseppina Andresini and Ib{\'e}ria Medeiros and Guilherme Gra{\c c}a and Lee Cooper and Naghmeh Ghazaleh and Jonas Richiardi and Diego Saldana and Konstantinos Sechidis and Arif Canakoglu and Sara Pido and Pietro Pinoli and Albert Bifet and Sepideh Pashami",

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Abdelqader, H, Smirnov, E, Pont, M & Geijselaers, M 2023, Interpretable and Reliable Rule Classification Based on Conformal Prediction. in I Koprinska, P Mignone, R Guidotti, S Jaroszewicz, H Fröning, F Gullo, PM Ferreira, D Roqueiro, G Ceddia, S Nowaczyk, J Gama, R Ribeiro, R Gavaldà, E Masciari, Z Ras, E Ritacco, F Naretto, A Theissler, P Biecek, W Verbeke, G Schiele, F Pernkopf, M Blott, I Bordino, IL Danesi, G Ponti, L Severini, A Appice, G Andresini, I Medeiros, G Graça, L Cooper, N Ghazaleh, J Richiardi, D Saldana, K Sechidis, A Canakoglu, S Pido, P Pinoli, A Bifet & S Pashami (eds), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings. vol. 1752, Springer International Publishing AG, Communications in Computer and Information Science, vol. 1752, pp. 385-401, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Grenoble, France, 19/09/22. https://doi.org/10.1007/978-3-031-23618-1_26

Interpretable and Reliable Rule Classification Based on Conformal Prediction. / Abdelqader, H.; Smirnov, E.; Pont, M. et al.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings. ed. / Irena Koprinska; Paolo Mignone; Riccardo Guidotti; Szymon Jaroszewicz; Holger Fröning; Francesco Gullo; Pedro M. Ferreira; Damian Roqueiro; Gaia Ceddia; Slawomir Nowaczyk; João Gama; Rita Ribeiro; Ricard Gavaldà; Elio Masciari; Zbigniew Ras; Ettore Ritacco; Francesca Naretto; Andreas Theissler; Przemyslaw Biecek; Wouter Verbeke; Gregor Schiele; Franz Pernkopf; Michaela Blott; Ilaria Bordino; Ivan Luciano Danesi; Giovanni Ponti; Lorenzo Severini; Annalisa Appice; Giuseppina Andresini; Ibéria Medeiros; Guilherme Graça; Lee Cooper; Naghmeh Ghazaleh; Jonas Richiardi; Diego Saldana; Konstantinos Sechidis; Arif Canakoglu; Sara Pido; Pietro Pinoli; Albert Bifet; Sepideh Pashami. Vol. 1752 Springer International Publishing AG, 2023. p. 385-401 (Communications in Computer and Information Science, Vol. 1752).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - Interpretable and Reliable Rule Classification Based on Conformal Prediction

AU - Abdelqader, H.

AU - Smirnov, E.

AU - Pont, M.

AU - Geijselaers, M.

PY - 2023

Y1 - 2023

N2 - This paper deals with the challenging problem of simultaneously integrating interpretablility and reliability into prediction models in machine learning. It proposes to combine the interpretable models of decision rules with the reliable models based on conformal prediction. The result is a new technique of conformal decision rules. Given a test instance, the technique is capable of providing a point prediction, an explanation, and a confidence value for that prediction plus a prediction set. The experiments show when and how conformal decision rules can be used for interpretable and reliable machine learning.

AB - This paper deals with the challenging problem of simultaneously integrating interpretablility and reliability into prediction models in machine learning. It proposes to combine the interpretable models of decision rules with the reliable models based on conformal prediction. The result is a new technique of conformal decision rules. Given a test instance, the technique is capable of providing a point prediction, an explanation, and a confidence value for that prediction plus a prediction set. The experiments show when and how conformal decision rules can be used for interpretable and reliable machine learning.

KW - Interpretable machine learning

KW - Reliable machine learning

KW - Decision rules

KW - Conformal prediction

U2 - 10.1007/978-3-031-23618-1_26

DO - 10.1007/978-3-031-23618-1_26

M3 - Chapter

SN - 9783031236174

VL - 1752

T3 - Communications in Computer and Information Science

SP - 385

EP - 401

BT - Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings

A2 - Koprinska, Irena

A2 - Mignone, Paolo

A2 - Guidotti, Riccardo

A2 - Jaroszewicz, Szymon

A2 - Fröning, Holger

A2 - Gullo, Francesco

A2 - Ferreira, Pedro M.

A2 - Roqueiro, Damian

A2 - Ceddia, Gaia

A2 - Nowaczyk, Slawomir

A2 - Gama, João

A2 - Ribeiro, Rita

A2 - Gavaldà, Ricard

A2 - Masciari, Elio

A2 - Ras, Zbigniew

A2 - Ritacco, Ettore

A2 - Naretto, Francesca

A2 - Theissler, Andreas

A2 - Biecek, Przemyslaw

A2 - Verbeke, Wouter

A2 - Schiele, Gregor

A2 - Pernkopf, Franz

A2 - Blott, Michaela

A2 - Bordino, Ilaria

A2 - Danesi, Ivan Luciano

A2 - Ponti, Giovanni

A2 - Severini, Lorenzo

A2 - Appice, Annalisa

A2 - Andresini, Giuseppina

A2 - Medeiros, Ibéria

A2 - Graça, Guilherme

A2 - Cooper, Lee

A2 - Ghazaleh, Naghmeh

A2 - Richiardi, Jonas

A2 - Saldana, Diego

A2 - Sechidis, Konstantinos

A2 - Canakoglu, Arif

A2 - Pido, Sara

A2 - Pinoli, Pietro

A2 - Bifet, Albert

A2 - Pashami, Sepideh

PB - Springer International Publishing AG

T2 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

Y2 - 19 September 2022 through 23 September 2022

ER -

Abdelqader H, Smirnov E, Pont M, Geijselaers M. Interpretable and Reliable Rule Classification Based on Conformal Prediction. In Koprinska I, Mignone P, Guidotti R, Jaroszewicz S, Fröning H, Gullo F, Ferreira PM, Roqueiro D, Ceddia G, Nowaczyk S, Gama J, Ribeiro R, Gavaldà R, Masciari E, Ras Z, Ritacco E, Naretto F, Theissler A, Biecek P, Verbeke W, Schiele G, Pernkopf F, Blott M, Bordino I, Danesi IL, Ponti G, Severini L, Appice A, Andresini G, Medeiros I, Graça G, Cooper L, Ghazaleh N, Richiardi J, Saldana D, Sechidis K, Canakoglu A, Pido S, Pinoli P, Bifet A, Pashami S, editors, Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Proceedings. Vol. 1752. Springer International Publishing AG. 2023. p. 385-401. (Communications in Computer and Information Science, Vol. 1752). doi: 10.1007/978-3-031-23618-1_26

Interpretable and Reliable Rule Classification Based on Conformal Prediction

Abstract

Publication series

Conference

Keywords

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