.png){kind=icon}
返回
Scalable Hyper-Ellipsoidal Function With Projection Ratio for Local Distributed Streaming Data Classification
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2997944.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Learning streaming data with limited size of memory storage becomes an interesting problem. Although there have been several learning methods recently proposed, based on the interesting concept of discard-after-learn, the performance of these issues: the learning speed, number of redundant neurons, and classification accuracy of these methods can be further improved in terms of faster speed, less number of neurons, and higher accuracy. The following new concepts and approaches were proposed in this paper: (1) a more generic structure of hyper-ellipsoidal function called Scalable Hyper-Ellipsoidal Function (SHEF) capable of handling the problem of a curse of dimensionality by introducing a regularization parameter into the covariance matrix of SHEF; (2) a new recursive function to update the covariance matrix of SHEF based on only the incoming data chunk; (3) a fast and easy conditions to test the states of being overlapped, inside, and touching of two SHEFs; (4) a new distance measure for determining the class of a queried datum based on the projected distance on only one discriminant vector, namely the Projection Ratio. The experimental results show the significant improvement when compared with the results from VLLDA, ILDA, LOL, VEBF, and CIL in terms of classification accuracy, the number of generated neurons, and computational time.
Keyword:
Neurons
Training data
Covariance matrices
Testing
Training
Memory management
Feature extraction
Streaming data classification
discriminant analysis
discard-after-learn
incremental learning
projection ratio
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams实时生物医学，医疗保健和健康数据流时代的转化生物信息学OAAI
OAAI分享收藏A model combining a Bayesian network with a modified genetic algorithm for green supplier selection.png)
SIMULATION
SIMULATIONIF0
PREAI
分享收藏
分享收藏分享收藏
查看更多内容