A new variant of Fuzzy K-Nearest Neighbor using Interval Type-2 Fuzzy Logic

被引：0

作者：

Melin, Patricia ^{[1
]}

Ramirez, Eduardo ^{[1
]}

Prado-Arechiga, German ^{[2
]}

机构：

[1] Tijuana Inst Technol, Div Grad Studies, Tijuana, BC, Mexico

[2] Excel Med Ctr, Cardiodiagnost, Tijuana, BC, Mexico

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | 2018年

关键词：

Fuzzy KNN; Mamdani Fuzzy Inference System; Interval Type-2 Fuzzy Logic; CARDIAC-ARRHYTHMIA CLASSIFICATION; SYSTEM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present a new variant of the Fuzzy K-Nearest Neighbor algorithm. We propose to use Interval Type-2 Fuzzy Logic to improve the performance of the Fuzzy K-Nearest Neighbor algorithm (Fuzzy KNN algorithm). We have used different measures to calculate the distance between the neighbors and the vector to be classified, such as Euclidean, Hamming, cosine similarity and city block distances. These distances represent the inputs for the Interval Type-2 Fuzzy Inference System. Simulation results show the potential of the proposed approach.

引用

页数：7

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