Fuzzy Restricted Boltzmann Machines

被引：0
|
作者：
Harrison, Robert W. [1 ]
Freas, Christopher [1 ]
机构：
[1] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA
来源：
FUZZY LOGIC IN INTELLIGENT SYSTEM DESIGN: THEORY AND APPLICATIONS | 2018年 / 648卷
关键词：
Fuzzy machine learning; Deep learning; Data mining; Energy-based learning; Restricted boltzmann machines;
D O I：
10.1007/978-3-319-67137-6-43
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Restricted Boltzmann Machines are a reconstructive neural network. They derive an implicitly probabilistic model of data which can be used to reconstruct or filter missing data as well as to classify data. This paper develops a deterministic training algorithm and shows how to use that algorithm to automatically derive fuzzy membership classes. The algorithm developed in this paper combines many of the best features of fuzzy learning algorithms and Restricted Boltzmann machines.
引用
收藏
页码：392 / 398
页数：7
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