Extraction of prototype-based threshold rules using neural training procedure

Marcin Blachnik; Mirosław Kordos; Włodzisław Duch

doi:10.1007/978-3-642-33266-1_32

Extraction of prototype-based threshold rules using neural training procedure

Marcin Blachnik
, Mirosław Kordos
, Włodzisław Duch

Department of Industrial Informatics (RM/RM4)

University of Bielsko-Biala
Nicolaus Copernicus University in Toruń
Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
Publisher	Springer Verlag
Pages	255-262
Number of pages	8
Edition	PART 2
ISBN (Print)	9783642332654
DOIs	https://doi.org/10.1007/978-3-642-33266-1_32
Publication status	Published - 2012
Event	22nd International Conference on Artificial Neural Networks, ICANN 2012 - Lausanne, Switzerland Duration: 11 Sept 2012 → 14 Sept 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7553 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Artificial Neural Networks, ICANN 2012
Country/Territory	Switzerland
City	Lausanne
Period	11/09/12 → 14/09/12

Keywords

Data understanding
prototype-based rules
rule extraction

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-33266-1_32

Cite this

Blachnik, M., Kordos, M., & Duch, W. (2012). Extraction of prototype-based threshold rules using neural training procedure. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings (PART 2 ed., pp. 255-262). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7553 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-642-33266-1_32

Blachnik, Marcin ; Kordos, Mirosław ; Duch, Włodzisław. / Extraction of prototype-based threshold rules using neural training procedure. Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2. ed. Springer Verlag, 2012. pp. 255-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Extraction of prototype-based threshold rules using neural training procedure",

abstract = "Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.",

keywords = "Data understanding, prototype-based rules, rule extraction",

author = "Marcin Blachnik and Miros{\l}aw Kordos and W{\l}odzis{\l}aw Duch",

year = "2012",

doi = "10.1007/978-3-642-33266-1\_32",

language = "English",

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booktitle = "Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings",

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Blachnik, M, Kordos, M & Duch, W 2012, Extraction of prototype-based threshold rules using neural training procedure. in Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7553 LNCS, Springer Verlag, pp. 255-262, 22nd International Conference on Artificial Neural Networks, ICANN 2012, Lausanne, Switzerland, 11/09/12. https://doi.org/10.1007/978-3-642-33266-1_32

Extraction of prototype-based threshold rules using neural training procedure. / Blachnik, Marcin; Kordos, Mirosław; Duch, Włodzisław.
Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2. ed. Springer Verlag, 2012. p. 255-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7553 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Extraction of prototype-based threshold rules using neural training procedure

AU - Blachnik, Marcin

AU - Kordos, Mirosław

AU - Duch, Włodzisław

PY - 2012

Y1 - 2012

N2 - Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.

AB - Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.

KW - Data understanding

KW - prototype-based rules

KW - rule extraction

UR - https://www.scopus.com/pages/publications/84867666564

U2 - 10.1007/978-3-642-33266-1_32

DO - 10.1007/978-3-642-33266-1_32

M3 - Conference contribution

AN - SCOPUS:84867666564

SN - 9783642332654

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 255

EP - 262

BT - Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings

PB - Springer Verlag

T2 - 22nd International Conference on Artificial Neural Networks, ICANN 2012

Y2 - 11 September 2012 through 14 September 2012

ER -

Blachnik M, Kordos M, Duch W. Extraction of prototype-based threshold rules using neural training procedure. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2 ed. Springer Verlag. 2012. p. 255-262. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-33266-1_32

Extraction of prototype-based threshold rules using neural training procedure

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