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Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining

Authors(2):

Kalyani Kathwadia, Aniket Patel
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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.

Kalyani Kathwadia, Aniket Patel

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 Print ISSN Online ISSN
2018-06-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
217-223 IJSRSET184861   Technoscience Academy

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.
URL : http://ijsrset.com/IJSRSET184861.php