A NEW FUZZY RULES WEIGHTING APPROACH BASED ON GENETIC PROGRAMMING FOR IMBALANCED CLASSIFICATION

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MAHDIZADEH MAHBOUBEH; EFTEKHARI MEHDI

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Journal: SIGNAL AND DATA PROCESSING Year:2015 | Volume:- | Issue:2 (SERIAL 22) Page(s): 111-125

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Information Journal Paper

Title

A NEW FUZZY RULES WEIGHTING APPROACH BASED ON GENETIC PROGRAMMING FOR IMBALANCED CLASSIFICATION

Author(s)

MAHDIZADEH MAHBOUBEH | EFTEKHARI MEHDI | Issue Writer Certificate

Keywords

IMBALANCED DATASET PROBLEMSQ2

FUZZY RULE-BASED CLASSIFICATION SYSTEMS (FRBCSS)Q2

WEIGHTING RULESQ2

GENETIC PROGRAMMINGQ2

Abstract

In classiﬁcation problems, we often encounter datasets with different percentage of patterns (i.e. classes with a high pattern percentage and classes with a low pattern percentage). These problems are called “classiﬁcation Problems with imbalanced data-sets”. Fuzzy rule based classification systems are the most popular fuzzy modeling systems used in pattern classification problems. Rule weights have been usually used to improve the classification accuracy and fuzzy versions of confidence and support merits have been widely used for rules weighting in fuzzy rule based classifiers. In this paper, we propose an evolutionary approach based on GENETIC PROGRAMMING to generate weighting expressions. For producing expressions confidence, support, lift and recall merits are used as terminals of GENETIC PROGRAMMING. Experiments are performed over 20 imbalanced KEEL's datasets and the results are analyzed using statistical tests. The results show that the proposed method improves the classification accuracy of FRBCS.

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APA: Copy

MAHDIZADEH, MAHBOUBEH, & EFTEKHARI, MEHDI. (2015). A NEW FUZZY RULES WEIGHTING APPROACH BASED ON GENETIC PROGRAMMING FOR IMBALANCED CLASSIFICATION. SIGNAL AND DATA PROCESSING, -(2 (SERIAL 22)), 111-125. SID. https://sid.ir/paper/160847/en

Vancouver: Copy

MAHDIZADEH MAHBOUBEH, EFTEKHARI MEHDI. A NEW FUZZY RULES WEIGHTING APPROACH BASED ON GENETIC PROGRAMMING FOR IMBALANCED CLASSIFICATION. SIGNAL AND DATA PROCESSING[Internet]. 2015;-(2 (SERIAL 22)):111-125. Available from: https://sid.ir/paper/160847/en

IEEE: Copy

MAHBOUBEH MAHDIZADEH, and MEHDI EFTEKHARI, “A NEW FUZZY RULES WEIGHTING APPROACH BASED ON GENETIC PROGRAMMING FOR IMBALANCED CLASSIFICATION,” SIGNAL AND DATA PROCESSING, vol. -, no. 2 (SERIAL 22), pp. 111–125, 2015, [Online]. Available: https://sid.ir/paper/160847/en

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