An Asymptotic Ensemble Learning Framework for Big Data Analysis

An Asymptotic Ensemble Learning Framework for Big Data Analysis

In order to enable big data analysis when data volume goes beyond the available computing resources, we propose a new method for big data analysis. This method uses only a few random sample data blocks of a big data set to obtain approximate results for the entire data set. The random sample partiti...

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Bibliographic Details
Main Authors: Salman Salloum, Joshua Zhexue Huang, Yulin He, Xiaojun Chen
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Big data analysis
cluster computing
random sample partition
block-level sampling
distributed and parallel computing
approximate computing
Online Access:https://ieeexplore.ieee.org/document/8586790/

Internet

https://ieeexplore.ieee.org/document/8586790/

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