Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework using Matlab
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@Article{JICS-12-141,
author = {Uma Mahesh Kumar Gandham and Dr P Suresh Varma},
title = {Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework using Matlab},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {12},
number = {2},
pages = {141--150},
abstract = {Data privacy protection is one of the most disturbed issues on the present industry Data isolation
issue require to be addressed immediately previous to the data sets are common on a cloud. Data point refers
to as hiding compound data for owner of data records. Expand the process of analysis over big
multidimensional information as well, by importance open problems and real investigate trends. In this
research new algorithm called Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce
Framework is been implemented on mat lab. Dispensation great quantity of information is attractive a
confronting for data investigation software. Data clustering is a documented information study technique in
data mining while adaptive K-Means is the well known partition clustering method. The inspiration at the
back ACMDDA proposing algorithm is to contract with different dimensional information clustering, with
minimum amount error rate and utmost meeting rate. With the help of multidimensional data set of map
dipping framework, here implemented algorithm will amplify the competence of the big data for out system.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22490.html}
}
TY - JOUR
T1 - Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework using Matlab
AU - Uma Mahesh Kumar Gandham and Dr P Suresh Varma
JO - Journal of Information and Computing Science
VL - 2
SP - 141
EP - 150
PY - 2024
DA - 2024/01
SN - 12
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22490.html
KW - Multi Dimension
KW - Cluster
KW - Data analysis
KW - Matlab
KW - K-means
KW - Map Reduce.
AB - Data privacy protection is one of the most disturbed issues on the present industry Data isolation
issue require to be addressed immediately previous to the data sets are common on a cloud. Data point refers
to as hiding compound data for owner of data records. Expand the process of analysis over big
multidimensional information as well, by importance open problems and real investigate trends. In this
research new algorithm called Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce
Framework is been implemented on mat lab. Dispensation great quantity of information is attractive a
confronting for data investigation software. Data clustering is a documented information study technique in
data mining while adaptive K-Means is the well known partition clustering method. The inspiration at the
back ACMDDA proposing algorithm is to contract with different dimensional information clustering, with
minimum amount error rate and utmost meeting rate. With the help of multidimensional data set of map
dipping framework, here implemented algorithm will amplify the competence of the big data for out system.
Uma Mahesh Kumar Gandham and Dr P Suresh Varma. (2024). Adaptive Cluster Multi Dimensional Data Analysis in Map Reduce Framework using Matlab.
Journal of Information and Computing Science. 12 (2).
141-150.
doi:
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