Learning fuzzy equivalence relation kernels with prior knowledge

Xiaoping Xue; Fengqiu Liu

doi:10.1109/ICMLC.2009.5212532

Learning fuzzy equivalence relation kernels with prior knowledge

Xiaoping Xue^*
, Fengqiu Liu

^*Corresponding author for this work

School of Mathematics

Harbin Institute of Technology

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

Abstract

This paper introduces a method of learning kernel by fuzzy equivalence relation (FER) based on prior knowledge. Firstly, prior knowledge is represented through fuzzy membership functions and fuzzy inference rules. Consequently features of prior knowledge are obtained by proper inference methods. Secondly, the learning rules of FER-kernel are obtained in terms of FER semantic interpretation and fuzzy inference. According to the proposed method, the representation of FER-kernel is incorporated with prior knowledge. Moreover, decision functions with the obtained FER-kernel generalize well with unseen examples corresponding to prior knowledge owing to the transitivity of FER-kernel with respect to triangular norm. Finally, some experiments of binary classification are conducted to demonstrate the performance of FRE-kernels in SVM.

Original language	English
Title of host publication	Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
Pages	237-242
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLC.2009.5212532
State	Published - 2009
Event	2009 International Conference on Machine Learning and Cybernetics - Baoding, China Duration: 12 Jul 2009 → 15 Jul 2009

Publication series

Name	Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
Volume	1

Conference

Conference	2009 International Conference on Machine Learning and Cybernetics
Country/Territory	China
City	Baoding
Period	12/07/09 → 15/07/09

Keywords

Fuzzy equivalence relation
Kernel
Prior knowledge

Access to Document

10.1109/ICMLC.2009.5212532

Cite this

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title = "Learning fuzzy equivalence relation kernels with prior knowledge",

abstract = "This paper introduces a method of learning kernel by fuzzy equivalence relation (FER) based on prior knowledge. Firstly, prior knowledge is represented through fuzzy membership functions and fuzzy inference rules. Consequently features of prior knowledge are obtained by proper inference methods. Secondly, the learning rules of FER-kernel are obtained in terms of FER semantic interpretation and fuzzy inference. According to the proposed method, the representation of FER-kernel is incorporated with prior knowledge. Moreover, decision functions with the obtained FER-kernel generalize well with unseen examples corresponding to prior knowledge owing to the transitivity of FER-kernel with respect to triangular norm. Finally, some experiments of binary classification are conducted to demonstrate the performance of FRE-kernels in SVM.",

keywords = "Fuzzy equivalence relation, Kernel, Prior knowledge",

author = "Xiaoping Xue and Fengqiu Liu",

year = "2009",

doi = "10.1109/ICMLC.2009.5212532",

language = "英语",

isbn = "9781424437030",

series = "Proceedings of the 2009 International Conference on Machine Learning and Cybernetics",

pages = "237--242",

booktitle = "Proceedings of the 2009 International Conference on Machine Learning and Cybernetics",

note = "2009 International Conference on Machine Learning and Cybernetics ; Conference date: 12-07-2009 Through 15-07-2009",

}

Xue, X & Liu, F 2009, Learning fuzzy equivalence relation kernels with prior knowledge. in Proceedings of the 2009 International Conference on Machine Learning and Cybernetics., 5212532, Proceedings of the 2009 International Conference on Machine Learning and Cybernetics, vol. 1, pp. 237-242, 2009 International Conference on Machine Learning and Cybernetics, Baoding, China, 12/07/09. https://doi.org/10.1109/ICMLC.2009.5212532

Learning fuzzy equivalence relation kernels with prior knowledge. / Xue, Xiaoping; Liu, Fengqiu.
Proceedings of the 2009 International Conference on Machine Learning and Cybernetics. 2009. p. 237-242 5212532 (Proceedings of the 2009 International Conference on Machine Learning and Cybernetics; Vol. 1).

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

TY - GEN

T1 - Learning fuzzy equivalence relation kernels with prior knowledge

AU - Xue, Xiaoping

AU - Liu, Fengqiu

PY - 2009

Y1 - 2009

N2 - This paper introduces a method of learning kernel by fuzzy equivalence relation (FER) based on prior knowledge. Firstly, prior knowledge is represented through fuzzy membership functions and fuzzy inference rules. Consequently features of prior knowledge are obtained by proper inference methods. Secondly, the learning rules of FER-kernel are obtained in terms of FER semantic interpretation and fuzzy inference. According to the proposed method, the representation of FER-kernel is incorporated with prior knowledge. Moreover, decision functions with the obtained FER-kernel generalize well with unseen examples corresponding to prior knowledge owing to the transitivity of FER-kernel with respect to triangular norm. Finally, some experiments of binary classification are conducted to demonstrate the performance of FRE-kernels in SVM.

AB - This paper introduces a method of learning kernel by fuzzy equivalence relation (FER) based on prior knowledge. Firstly, prior knowledge is represented through fuzzy membership functions and fuzzy inference rules. Consequently features of prior knowledge are obtained by proper inference methods. Secondly, the learning rules of FER-kernel are obtained in terms of FER semantic interpretation and fuzzy inference. According to the proposed method, the representation of FER-kernel is incorporated with prior knowledge. Moreover, decision functions with the obtained FER-kernel generalize well with unseen examples corresponding to prior knowledge owing to the transitivity of FER-kernel with respect to triangular norm. Finally, some experiments of binary classification are conducted to demonstrate the performance of FRE-kernels in SVM.

KW - Fuzzy equivalence relation

KW - Kernel

KW - Prior knowledge

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U2 - 10.1109/ICMLC.2009.5212532

DO - 10.1109/ICMLC.2009.5212532

M3 - 会议稿件

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SN - 9781424437030

T3 - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics

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BT - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics

T2 - 2009 International Conference on Machine Learning and Cybernetics

Y2 - 12 July 2009 through 15 July 2009

ER -

Learning fuzzy equivalence relation kernels with prior knowledge

Abstract

Publication series

Conference

Keywords

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