Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining

Authors(2) :-Kalyani Kathwadia, Aniket Patel

Datasets is very challenging task in the systems. It is real processing. Data mining technique classification is one of the most important technique, in this paper is to classify the data as improve the classification accuracy, we have used ensemble model for classification of data. Randomization process added to privacy sensitive data after next process reconstruction to the main data from the perturbed data. Principal Component Analysis (PCA) is used to preserve the variability in the data. Rotation transformation can enlarge the increase the base classifiers and improve the accuracy of the ensemble classifier. In this paper, we analyses a rotation perturbation technique for PCA find eigenvector, load line plot and Zscore-Normalization method using to dimension in stream mining.

Authors and Affiliations

Kalyani Kathwadia
Department of Information Technology Silver Oak College of Engineering And Technology Ahmedabad, Gujarat, India
Aniket Patel
Department of Information Technology Silver Oak College of Engineering And Technology Ahmedabad, Gujarat, India

Data mining, Classification, Privacy, PCA, Z score-Normalization

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Publication Details

Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 217-223
Manuscript Number : IJSRSET184861
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Kalyani Kathwadia, Aniket Patel, " Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.217-223, May-June-2018.
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