2019 VOL.2 Apr No.2

• Title: High-Dimensional Big Data Subspace Clustering Integrated Processing Method Based on Cloud Computing
• Name: Anthony Hill
• Company: The University of Auckland, Auckland, New Zealan
• Abstract:

  In the field of data mining, high-dimensional data is generally sparse, there are a lot of redundant dimension, it is easy to cover the real structure of the data. Therefore, based on the high-dimensional data of a large cloud, subspace clustering to study the integration processing method. Features tend to have high dimensional data redundancy. These characteristics affect the accuracy of the redundant cluster, increasing the time complexity of the algorithm. If the advance of the high-dimensional feature selection data to select a proper subset of features, can effectively reduce the complexity of the process time and improve the accuracy of analysis results. Subspace clustering integrated approach is a way to analyze the problem of computer learning more learners integrate.

• Keyword: Keywords: cloud computing; subspace; integration; method
• DOI: 10.12250/jpciams2019020114
• Citation form: Anthony Hill.High-Dimensional Big Data Subspace Clustering Integrated Processing Method Based on Cloud Computing[J]. Computer Informatization and Mechanical System, 2019, vol. 2, pp. 12-18.

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